无线传感器网络覆盖控制技术研究
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摘要
无线传感网络(Wireless Sensor Networks, WSNs)在新一代网络中具有关键性角色,作为一种新的计算模式,推动科技发展和社会进步,已成为国际竞争的焦点和制高点,关系到国家政治、经济和社会的安全。在无线传感器网络应用中,覆盖反映了网络对物理世界的监测能力,常作为描述无线传感器网络监测服务质量(Quality of Service, QoS)的标准,是无线传感器网络应用的基础。由于应用规模大,能量、计算能力和通信能力受限等特点,往往在监测区域内对传感器节点进行大规模、高密度部署,这就造成部署代价与部署质量、节点能量受限与网络生存时间之间的矛盾。覆盖控制通过对节点感知能力的建模,结合具体应用要求,在监测区域内部署传感器节点,使其能有效的获取监测区域的信息;在不影响网络覆盖性能的前提下,合理调度节点状态以减少网络中活跃节点数量,延长网络生存时间;最终使传感器网络的各种资源得到有效利用,网络监控服务质量得到改善。
本文深入研究无线传感器网络覆盖控制技术,开展无线传感器网络节点部署和节点调度问题研究。本文主要工作和贡献如下:
1)提出两种覆盖保证的节点随机部署策略:平均面积覆盖部署策略和边界辅助部署策略,以解决节点部署中边界效应造成的覆盖过高估计问题,满足实际部署中覆盖质量要求。部署质量和部署代价是无线传感器网络相矛盾的两个方面。网络的成功应用依赖于节点部署中所达到的覆盖质量,即用较少的节点达到所期望的覆盖要求。通常用渐近性分析来求出满足覆盖要求的最少节点数。然而,由于存在覆盖过高估计问题,这种渐近性分析在实际的部署中难以达到部署要求。针对该问题,提出两种覆盖保证的节点部署策略:平均面积覆盖部署策略ECD(Expected-area Coverage Deployment)和边界辅助部署策略BOAD(BOundary Assistant Deployment)。从理论上对两种部署策略进行分析,给出满足部署要求节点个数的下限值。通过理论分析与仿真验证两种部署策略正确性和有效性。仿真结果表明,两种部署策略有效的缓解了覆盖过高估计问题。在目标检测应用中验证了两种部署策略的优势,并把两种部署策略扩展到一般监测区域和节点概率感知模型中。
2)提出一种距离辅助的节点覆盖冗余判别模型,节点只需要获得与邻居的距离信息,就可以精确判别被邻居节点覆盖的程度。并在此基础上提出非均匀分布的无线传感器节点调度机制。针对传统依赖精确位置信息的复杂计算和无位置信息部署受限等弊端,从理论上对节点部署方式进行分析。在节点位置信息未知情况下,提出距离辅助的节点覆盖判别模型DANCI(Distance-Assistant Node Coverage Identification model),通过邻居节点到本节点的距离信息,判别该节点被邻居节点覆盖的程度。并在此基础上提出一种非均匀分布下的无线传感器网络节点调度机制NDNS(Non-uniform Distribution Node Scheduling),该机制利用距离辅助的节点覆盖判别模型,对节点覆盖冗余进行判别,适应于任意分布下的网络部署方式。仿真结果表明,在节点随机部署情况下,计算所得的覆盖冗余与节点位置已知情况下的最大误差仅为6.3960%。在保证网络覆盖的前提下,有效的延长了网络的生存时间。
3)提出一种基于容忍覆盖区域的节点调度算法,解决位置信息未知条件下,由于不均等休眠带来的调度洞问题。位置信息未知的节点调度算法以节点的感知区域覆盖为调度目标,导致处于边界区域的节点由于没有太多机会进入休眠状态而先死亡,进而引起死亡节点向监测中心扩散现象;或者监测区域中心某些孤立节点由于没有太多机会休眠先死亡,引起死亡节点由监测区域中心向外部扩散现象,我们称这种现象为“不均等休眠”带来的调度洞问题。针对该问题,从理论上对节点覆盖模型进行分析,提出容忍覆盖区域的概念,并在此基础上设计一种基于容忍覆盖区域的节点调度算法。仿真结果表明,基于容忍覆盖区域的节点调度算法能够缓解“不均等休眠”现象,解决了由边界节点或孤立节点过早死亡造成的能量消耗不平衡问题,有效的延长了网络的生存时间。
4)提出在实际应用场景中入侵目标至少被k个节点立刻检测到的理论模型,分析外界环境等因素对节点感知能力的影响,得出目标入侵监测区域时被检测到的概率。
目标检测和环境检测是传感器网络的重要应用之一。节点的监测质量可以通过入侵目标穿越监测区域时被检测的概率来衡量,节点检测的概率为监测质量和决策提供基础。然而,在实际的网络部署和应用场景中,节点的感知能力通常受到阴影衰落及路径损失的影响。在此情况下,提出在实际应用场景中入侵目标至少被k个节点检测到的理论模型,并详细分析了节点在阴影衰落与理想感知检测两种情况下的检测概率,进而说明理想的感知检测与实际应用中检测概率的明显差异。通过该理论分析模型可以有效的估计出节点在具体的应用场景下的监测性能。
Wireless Sensor Networks (WSNs) play an important role in next generation networks. As an emerging technology with great potential to drive the development of science and technology, promote the advancement of society, and impact national politics and security, WSNs have become a primary focus of international competitors. In wireless sensor networks applications, network coverage reflects an ability of monitoring the physical world, often as a description to monitor standards of the quality of service (Quality of Service, QoS). As the application characteristic for large scale, the energy constraints, with limited computing ability and communication ability. The sensor nodes are often deployed with large-scale, high-density in monitored region, which brings conflicts between deployment costs and deployment quality, the energy constraints of nodes and network lifetime. Coverage control by modeling the sensing ability of sensor nodes, combined with application requirements, effectively obtain information in monitoring area by deployment of sensor nodes. And without sacrificing system original performance by putting some sensor nodes into active state for the sensing and communication tasks while other sensor nodes remain low-power sleep state. The network lifetime is prolonged by efficiently using a variety of resources. Finally, the QoS is improved in monitored region.
In this dissertation, we mainly focus on coverage control problems in wireless sensor networks. The outline of this dissertation is described as follows:
1) Two coverage-guaranteed sensor node deployment strategies for wireless sensor networks are proposed to overcome coverage overestimation problem induced by border effects. Eg. Expected-area Coverage Deployment (ECD) and BOundary
Assistant Deployment (BOAD), and then coverage quality requirements can be satisfied in real deployment. Deployment quality and cost are two conflicting aspects in wireless sensor networks. Their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. To overcome this problem, we propose two deployment strategies, namely, the expected-area coverage deployment strategy and boundary assistant deployment strategy. The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region. The general monitored region and probabilistic sensing model are extended for two deployment strategies.
2) A distance-assistant node coverage identification model is proposed by using distance information between the node and its neighbors to identify nodes coverage without using any location information. The coverage degree can accurately determined by the neighbor nodes. Based on this model, a NDNS (Non-uniform Distribution Node
Scheduling) is proposed which satisfies with different random distribution. Aiming at the defect that high computational complexity of exact location information and the distribution limitation of location information-free in traditional schemes, the node distribution is analyzed theoretically. A distance-assistant node coverage identification model(DANCI) is proposed which adopts distance information between the node and its neighbors to identify nodes coverage without using any location information. A node scheduling scheme NDNS based on DANCI is proposed which satisfies with different random distribution. Theory analysis and simulation results are presented to evaluate the proposed DANCI model. It is shown that in randomly deployed sensor networks, the maximum coverage error is 6.396 0% between DANCI model and location information-aware strategy. The numerical experiments results illustrate that the longer network lifetime is achieved in preserving networks coverage.
3) A node scheduling scheme based on tolerable coverage area is proposed. The node scheduling problem conduced by the inequality sleeping in location-free conditions is alleviated by proposed algorithm. Traditional methods of node scheduling without location information are aiming at node sensing area coverage. It leads to nodes in the border of monitored region or some nodes without neighbors in monitored region die first due to having no chance to enter sleep state, and then the death spreads to the central region. We call this phenomenon as inequality sleep problems. To address this problem, from the theoretical analysis of the sensor node coverage model, we propose the concept of tolerable coverage area, and a node scheduling scheme based on tolerable coverage area. Simulation results demonstrate that the proposed method not only alleviates the inequality sleep problems, but also prolongs network lifetime.
4) An intrusion detection model is suggested, in which the intruder can be detected immediately by at least k sensor nodes under practical considerations. The problem that the sensing capabilities of sensors are affected by environmental factors in real deployment is investigated. The detection probability by at least k sensors under practical considerations is studied. Target detection and field surveillance are among the most prominent applications of wireless sensor networks. The quality of detection achieved by a sensor network can be quantified by evaluating the probability of detecting a mobile target crossing a sensing field. Detection probability of sensor nodes has been studied in sensor networks for many purposes such as quality of service and decision-making. However, the sensing capabilities of sensors are affected by environmental factors in real deployment. The problem of detecting probability in a log-normal shadow fading environment is investigated. It presents an analytic method to evaluate the detection probability by at least k sensors under practical considerations. Furthermore, we also shows that shadow fading makes significant influence in detection probability compared to unit disk sensing model through extensive simulation experiments.
本文深入研究无线传感器网络覆盖控制技术,开展无线传感器网络节点部署和节点调度问题研究。本文主要工作和贡献如下:
1)提出两种覆盖保证的节点随机部署策略:平均面积覆盖部署策略和边界辅助部署策略,以解决节点部署中边界效应造成的覆盖过高估计问题,满足实际部署中覆盖质量要求。部署质量和部署代价是无线传感器网络相矛盾的两个方面。网络的成功应用依赖于节点部署中所达到的覆盖质量,即用较少的节点达到所期望的覆盖要求。通常用渐近性分析来求出满足覆盖要求的最少节点数。然而,由于存在覆盖过高估计问题,这种渐近性分析在实际的部署中难以达到部署要求。针对该问题,提出两种覆盖保证的节点部署策略:平均面积覆盖部署策略ECD(Expected-area Coverage Deployment)和边界辅助部署策略BOAD(BOundary Assistant Deployment)。从理论上对两种部署策略进行分析,给出满足部署要求节点个数的下限值。通过理论分析与仿真验证两种部署策略正确性和有效性。仿真结果表明,两种部署策略有效的缓解了覆盖过高估计问题。在目标检测应用中验证了两种部署策略的优势,并把两种部署策略扩展到一般监测区域和节点概率感知模型中。
2)提出一种距离辅助的节点覆盖冗余判别模型,节点只需要获得与邻居的距离信息,就可以精确判别被邻居节点覆盖的程度。并在此基础上提出非均匀分布的无线传感器节点调度机制。针对传统依赖精确位置信息的复杂计算和无位置信息部署受限等弊端,从理论上对节点部署方式进行分析。在节点位置信息未知情况下,提出距离辅助的节点覆盖判别模型DANCI(Distance-Assistant Node Coverage Identification model),通过邻居节点到本节点的距离信息,判别该节点被邻居节点覆盖的程度。并在此基础上提出一种非均匀分布下的无线传感器网络节点调度机制NDNS(Non-uniform Distribution Node Scheduling),该机制利用距离辅助的节点覆盖判别模型,对节点覆盖冗余进行判别,适应于任意分布下的网络部署方式。仿真结果表明,在节点随机部署情况下,计算所得的覆盖冗余与节点位置已知情况下的最大误差仅为6.3960%。在保证网络覆盖的前提下,有效的延长了网络的生存时间。
3)提出一种基于容忍覆盖区域的节点调度算法,解决位置信息未知条件下,由于不均等休眠带来的调度洞问题。位置信息未知的节点调度算法以节点的感知区域覆盖为调度目标,导致处于边界区域的节点由于没有太多机会进入休眠状态而先死亡,进而引起死亡节点向监测中心扩散现象;或者监测区域中心某些孤立节点由于没有太多机会休眠先死亡,引起死亡节点由监测区域中心向外部扩散现象,我们称这种现象为“不均等休眠”带来的调度洞问题。针对该问题,从理论上对节点覆盖模型进行分析,提出容忍覆盖区域的概念,并在此基础上设计一种基于容忍覆盖区域的节点调度算法。仿真结果表明,基于容忍覆盖区域的节点调度算法能够缓解“不均等休眠”现象,解决了由边界节点或孤立节点过早死亡造成的能量消耗不平衡问题,有效的延长了网络的生存时间。
4)提出在实际应用场景中入侵目标至少被k个节点立刻检测到的理论模型,分析外界环境等因素对节点感知能力的影响,得出目标入侵监测区域时被检测到的概率。
目标检测和环境检测是传感器网络的重要应用之一。节点的监测质量可以通过入侵目标穿越监测区域时被检测的概率来衡量,节点检测的概率为监测质量和决策提供基础。然而,在实际的网络部署和应用场景中,节点的感知能力通常受到阴影衰落及路径损失的影响。在此情况下,提出在实际应用场景中入侵目标至少被k个节点检测到的理论模型,并详细分析了节点在阴影衰落与理想感知检测两种情况下的检测概率,进而说明理想的感知检测与实际应用中检测概率的明显差异。通过该理论分析模型可以有效的估计出节点在具体的应用场景下的监测性能。
Wireless Sensor Networks (WSNs) play an important role in next generation networks. As an emerging technology with great potential to drive the development of science and technology, promote the advancement of society, and impact national politics and security, WSNs have become a primary focus of international competitors. In wireless sensor networks applications, network coverage reflects an ability of monitoring the physical world, often as a description to monitor standards of the quality of service (Quality of Service, QoS). As the application characteristic for large scale, the energy constraints, with limited computing ability and communication ability. The sensor nodes are often deployed with large-scale, high-density in monitored region, which brings conflicts between deployment costs and deployment quality, the energy constraints of nodes and network lifetime. Coverage control by modeling the sensing ability of sensor nodes, combined with application requirements, effectively obtain information in monitoring area by deployment of sensor nodes. And without sacrificing system original performance by putting some sensor nodes into active state for the sensing and communication tasks while other sensor nodes remain low-power sleep state. The network lifetime is prolonged by efficiently using a variety of resources. Finally, the QoS is improved in monitored region.
In this dissertation, we mainly focus on coverage control problems in wireless sensor networks. The outline of this dissertation is described as follows:
1) Two coverage-guaranteed sensor node deployment strategies for wireless sensor networks are proposed to overcome coverage overestimation problem induced by border effects. Eg. Expected-area Coverage Deployment (ECD) and BOundary
Assistant Deployment (BOAD), and then coverage quality requirements can be satisfied in real deployment. Deployment quality and cost are two conflicting aspects in wireless sensor networks. Their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. To overcome this problem, we propose two deployment strategies, namely, the expected-area coverage deployment strategy and boundary assistant deployment strategy. The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region. The general monitored region and probabilistic sensing model are extended for two deployment strategies.
2) A distance-assistant node coverage identification model is proposed by using distance information between the node and its neighbors to identify nodes coverage without using any location information. The coverage degree can accurately determined by the neighbor nodes. Based on this model, a NDNS (Non-uniform Distribution Node
Scheduling) is proposed which satisfies with different random distribution. Aiming at the defect that high computational complexity of exact location information and the distribution limitation of location information-free in traditional schemes, the node distribution is analyzed theoretically. A distance-assistant node coverage identification model(DANCI) is proposed which adopts distance information between the node and its neighbors to identify nodes coverage without using any location information. A node scheduling scheme NDNS based on DANCI is proposed which satisfies with different random distribution. Theory analysis and simulation results are presented to evaluate the proposed DANCI model. It is shown that in randomly deployed sensor networks, the maximum coverage error is 6.396 0% between DANCI model and location information-aware strategy. The numerical experiments results illustrate that the longer network lifetime is achieved in preserving networks coverage.
3) A node scheduling scheme based on tolerable coverage area is proposed. The node scheduling problem conduced by the inequality sleeping in location-free conditions is alleviated by proposed algorithm. Traditional methods of node scheduling without location information are aiming at node sensing area coverage. It leads to nodes in the border of monitored region or some nodes without neighbors in monitored region die first due to having no chance to enter sleep state, and then the death spreads to the central region. We call this phenomenon as inequality sleep problems. To address this problem, from the theoretical analysis of the sensor node coverage model, we propose the concept of tolerable coverage area, and a node scheduling scheme based on tolerable coverage area. Simulation results demonstrate that the proposed method not only alleviates the inequality sleep problems, but also prolongs network lifetime.
4) An intrusion detection model is suggested, in which the intruder can be detected immediately by at least k sensor nodes under practical considerations. The problem that the sensing capabilities of sensors are affected by environmental factors in real deployment is investigated. The detection probability by at least k sensors under practical considerations is studied. Target detection and field surveillance are among the most prominent applications of wireless sensor networks. The quality of detection achieved by a sensor network can be quantified by evaluating the probability of detecting a mobile target crossing a sensing field. Detection probability of sensor nodes has been studied in sensor networks for many purposes such as quality of service and decision-making. However, the sensing capabilities of sensors are affected by environmental factors in real deployment. The problem of detecting probability in a log-normal shadow fading environment is investigated. It presents an analytic method to evaluate the detection probability by at least k sensors under practical considerations. Furthermore, we also shows that shadow fading makes significant influence in detection probability compared to unit disk sensing model through extensive simulation experiments.
引文
[1] Akyildiz I F, Su W, Sankarasubramaniam Y, et al. Wireless sensor networks: a survey [J]. Computer Networks, 2002, 38(4): 393-422.
[2]任丰原,黄海宁,林闯.无线传感器网络[J].软件学报, 2003, 14(7): 1282-1291.
[3]孙利民,李建中,陈渝等.无线传感器网络[M].北京;清华大学出版社. 2005.
[4]李建中,李金宝,石胜飞.传感器网络及其数据管理的概念、问题与进展[J].软件学报, 2003, 14(10): 1717-1727.
[5]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报, 2004, 25(4): 114-124.
[6] SmartDust. Available from: http: //robotics. eecs. berkeley. edu/~pister/SmartDust/.
[7] Simon G, Maróti M, Lédeczi, et al. Sensor network-based countersniper system[A]. Proceedings of the 2nd international conference on Embedded networked sensor systems[C], Baltimore, MD, USA, ACM, 2004:1-12.
[8] Paul J L. Smart Sensor Web: Web-based exploitation of sensor fusion for visualization of the tactical battlefield [J]. IEEE Aerospace and Electronic Systems Magazine, 2001, 16(5): 29-36.
[9] Liang S H L, Croitoru A, Tao C V. A distributed geospatial infrastructure for Sensor Web [J]. Computers & Geosciences, 2005, 31(2): 221-231.
[10] Polastre J. Design and implementation of wireless sensor networks for habitat monitoring [D]. Berkeley: University of California, 2003.
[11] Bonnet P, Gehrke J, Seshadri P. Querying the physical world [J]. IEEE Personal Communications, 2000, 7, 10-15.
[12] Tia G, Greenspan D, Welsh M, et al. Vital Signs Monitoring and Patient Tracking Over a Wireless Network[A]. Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society( EMBS)[C], 2005:102-105.
[13] SSIM. Available from: http: //www. ssim. eng. wayne. edu/.
[14] Meyer S, Rakotonirainy A. A survey of research on context-aware homes[A]. Proceedings of the Australasian information security workshop conference on ACSW frontiers [C], Adelaide, Australia, Australian Computer Society, Inc., 2003.
[15] Noury N, Herve T, Rialle V, et al. Monitoring behavior in home using a smart fall sensor and position sensors[A]. Proceedings of the 1st Annual International, Conference on Microtechnologies in Medicine and Biology[C], Lyon, France, 2000:607-610.
[16] Xu N, Rangwala S, Chintalapudi K K, et al. A wireless sensor network For structural monitoring[A]. Proceedings of the 2nd international conference on Embedded networked sensor systems[C], Baltimore, MD, USA, ACM, 2004:13-24.
[17] Coleri S, Cheung S, Varaiya P. Sensor networks for monitoring traffic[A]. Proceedings of the Allerton Conference on Communication, Control and Computing[C]. 2004:32–40.
[18] Karpiriski M, Senart A, Cahill V. Sensor networks for smart roads[A]. Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops(PerCom)[C], 2006:5-310.
[19] Callaway E H. wireless sensor networks: architectures and protocols [M]. Boca Raton Florida; CRC Press LLC. 2004.
[20] Rashid R F, Robertson G G. Accent: A communication oriented network operating system kernel [J]. SIGOPS Operating Systems Review, 1981, 15(5): 64-75.
[21] Rashid R, Julin D, Orr D, et al. Mach: a system software kernel[A]. Proceedings of the Thirty-FourthIEEE Computer Society International Conference: Intellectual Leverage, Digest of Papers[C], 1989:176-178.
[22] Myers C, Oppenheim A, Davis R, et al. Knowledge based speech analysis and enhancement[A]. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP '84)[C], 1984:162-165.
[23] Lacoss R T. Distributed Mixed Sensor Aircraft Tracking[A]. Proceedings of the American Control Conference[C], Minneapolis, MN, USA, 1987:1827-1830.
[24] D. Alberts J G, F. Stein. Network Centric Warfare, 1999. Http://Www.Dodccrp.Org/Publications/Pdf/Alberts Ncw.Pdf.
[25] SensIT. Available from: http://www.sainc.com/sensit/.
[26] ALERT System. Available from: http://www.altersystem.org/.
[27] Habitat Monitoring on Great Duck Island. Available from: http://www.greatduckisland.net.
[28] Schwiebert L, Gupta S K S, Weinmann J. Research challenges in wireless networks of biomedical sensors[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:151-165.
[29] AHRI Project. Available from: http://www.cc.gatech.edu/fce/ahri.
[30] NASA/JPL Sensor Webs Project. Available from: http://sensorwebs.jpl.nasa.gov/.
[31] EECS. Available from: http://bwrc.eecs.berkeley.edu.
[32] WEBS. Available from: http://webs.cs.berkeley.edu.
[33] CENS. Available from: http://research.cens.ucla.edu.
[34] WINS. Available from: http://www.janet.ucla.edu.
[35] NMS. Available from: http://nms.csail.mit.edu.
[36] ENALAB. Available from: http://www.eng.yale.edu/enalab.
[37] MICA. Available from: http://www/xbow.com/products/wireless_sensor_networks.htm.
[38] PicoNode. Available from: http://bwrc.eecs.berkeley.edu/research/pico_radio/default.htm.
[39] TinyOS. Available from: http://www.tinyos.net.
[40] MANTIS. Available from: http://mantis.cs.colorado.edu/index.php/tiki-index.php.
[41] SOS. Available from: http://nesl.ee.ucla.edu/projects/sos/.
[42] Meguerdichian S, Koushanfar F, Potkonjak M, et al. Coverage problems in wireless ad-hoc sensor networks[A]. Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM'01)[C], 2001:1380-1387
[43] Wang B, Wang W, Srinivasan V, et al. Information coverage for wireless sensor networks [J]. IEEE Communications Letters, 2005, 9(11): 967-969.
[44] Cardei M W J. Coverage in wireless sensor networks [M]. Ilyas M, Magboub I, eds: CRC Press, 2004.
[45] Bang W. Coverage control in sensor networks [M]. Computer Communications and Networks. 2010.
[46]任彦,张思东,张宏科.无线传感器网络中覆盖控制理论与算法[J].软件学报, 2006, 17(3): 422-433.
[47]任彦.无线传感器网络覆盖与拓扑控制理念与技术研究[D].北京:北京交通大学, 2008.
[48]蒋杰,方力,张鹤颖等.无线传感器网络最小连通覆盖集问题求解[J].软件学报, 2006, 17(2): 175-184.
[49]刘丽萍.无线传感器网络节能覆盖[D].杭州:浙江大学, 2006.
[50] Chakrabarty K, Iyengar S, Qi H, et al. Grid coverage for surveillance and target location in distributed sensor networks [J]. IEEE Transactions on Computers, 2002, 51(12): 1448-1453.
[51] Chakrabarty K, Iyengar S S, Hairong Q, et al. Coding theory framework for target location in distributed sensor networks[A]. Proceedings of the International Conference on Information Technology: Coding and Computing[C], Washington, DC, USA IEEE Computer Society2001:130-134.
[52] Zou Y. Coverage-driven sensor deployment and energy-efficient information processing in wireless sensor networks [D]: Duke University, 2004.
[53] Zou Y, Chakrabarty K. Uncertainty-aware and coverage-oriented deployment for sensor networks [J]. Journal of Parallel and Distributed Computing, 2004, 64(7): 788-798.
[54] Zou Y, Chakrabarty K. Sensor deployment and target localization in distributed sensor networks [J]. ACM Transactions on Embedded Computing Systems (TECS), 2004, 3(1): 61-91.
[55]蒋杰.无线传感器网络覆盖控制研究[D].长沙:国防科学技术大学, 2005.
[56] Veltri G, Huang Q, Qu G, et al. Minimal and maximal exposure path algorithms for wireless embedded sensor networks[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA ACM, 2003:40-50.
[57] Meguerdichian S, Koushanfar F, Qu G, et al. Exposure in wireless Ad-Hoc sensor networks[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:139-150
[58] Ma H, Liu Y. Some problems of directional sensor networks [J]. International Journal of Sensor Networks, 2007, 2(1): 44-52.
[59] Ma H, Liu Y. On coverage problems of directional sensor networks [J]. Mobile Ad-hoc and Sensor Networks, 2005, 721-731.
[60] Clouqueur T, Phipatanasuphorn V, Ramanathan P, et al. Sensor deployment strategy for detection of targets traversing a region [J]. Mobile Networks and Applications, 2003, 8(4): 453-461.
[61] Venkataraman J, Haenggi M, Collins O. Shot noise models for the dual problems of cooperative coverage and outage in random networks[A]. Proceedings of the 44th Annual Allerton Conference on Communication, Control, and Computing (Allerton)[C], Monticello, IL, 2006:1-10.
[62] Rui W, Wenming C. Universal information coverage for bandwidth-constrained sensor networks[A]. Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO)[C], Sanya, China, 2007:904-907.
[63] Xing G, Tan R, Liu B, et al. Data fusion improves the coverage of wireless sensor networks[A]. Proceedings of the 15th annual international conference on Mobile computing and networking[C], Beijing, China, ACM, 2009:157-168.
[64] Ming-Chen Z, Jiayin L, Min-You W, et al. Surface Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE INFOCOM 2009[C], 2009:109-117.
[65]张学,陆桑璐,陈贵海等.无线传感器网络的拓扑控制[J].软件学报, 2007, 18(4): 943-954.
[66] Kenan X. Device Deployment Strategies for Large-scale Wireless Sensor Networks [D]: QSpace at Queen's University, 2008.
[67] Younis O, Fahmy S. HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks [J]. IEEE Transactions on Mobile Computing, 2004, 366-379.
[68] Mhatre V, Rosenberg C, Kofman D, et al. A minimum cost heterogeneous sensor network with a lifetime constraint [J]. IEEE Transactions on Mobile Computing, 2005, 4-15.
[69] Younis M, Akkaya K. Strategies and techniques for node placement in wireless sensor networks: A survey [J]. Ad Hoc Networks, 2008, 6(4): 621-655.
[70] Romer K, Mattern F. The design space of wireless sensor networks[J]. IEEE Wireless Communications, 2004, 11(6): 54-61.
[71] O’rourke J. Art Gallery Theorems and Algorithms. The International Series of Monographs on Computer Science [M]. Oxford University Press, New York, NY. 1987.
[72] Shakkottai S, Srikant R, Shroff N. Unreliable sensor grids: Coverage, connectivity and diameter [J]. Ad Hoc Networks, 2005, 3(6): 702-716.
[73] Coskun V. Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks [J]. Sensors, 2008, 8, 2792-2817.
[74]王晓东.无线传感器网络节能算法研究[D].杭州:浙江大学, 2007.
[75] Tilak S, Abu-Ghazaleh NB, Heinzelman W. Infrastructure trade-offs for sensor networks. Proceedings of First InternationalWorkshop on Wireless Sensor Networks and Applications (WSNA'02), 2002: 49-57.
[76] Balister P, Bollobas B, Sarkar A, et al. Reliable density estimates for coverage and connectivity in thin strips of finite length[A]. Proceedings of the 13th annual ACM international conference on Mobile computing and networking [C], Montréal, Québec, Canada, ACM, 2007:75-86.
[77] González-Banos H. A randomized art-gallery algorithm for sensor placement [M]. Proceedings of the seventeenth annual symposium on Computational geometry. Medford, Massachusetts, United States, ACM. 2001: 232-240.
[78] Zhang H, Hou J C. Is Deterministic Deployment Worse than Random Deployment for Wireless Sensor Networks?[A]. Proceedings of the 25th IEEE International Conference on Computer Communications[C], Barcelona, Spain, 2006:1-13.
[79] Onur E, Ersoy C, Delic H. How many sensors for an acceptable breach detection probability? [J]. Computer communications, 2006, 29(2): 173-182.
[80] Balister P, Kumar S. Random vs. Deterministic Deployment of Sensors in the Presence of Failures and Placement Errors[A]. Proceedings of the IEEE INFOCOM 2009[C], 2009:2896-2900.
[81] Leoncini M, Resta G, Santi P. Partially controlled deployment strategies for wireless sensors [J]. Ad Hoc Networks, 2009, 7(1): 1-23.
[82] Leow W L, Pishro-Nik H. Results on coverage for finite wireless networks[A]. Proceedings of the 2007 international conference on Wireless communications and mobile computing[C], Honolulu, Hawaii, USA, ACM, 2007:364-369
[83] Clouqueur T, Phipatanasuphorn V, Ramanathan P, et al. Sensor deployment strategy for target detection[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:42-48.
[84] Hou Y, Chen C, Jeng B. An optimal new-node placement to enhance the coverage of wireless sensor networks [J]. Wireless Networks, 16(4): 1033-1043.
[85]刘明,曹建农,郑源等.无线传感器网络多重覆盖问题分析[J].软件学报, 2007, 28(1): 125-136.
[86] Bredin J L, Demaine E D, Hajiaghayi M, et al. Deploying sensor networks with guaranteed capacity and fault tolerance[A]. Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing[C], Urbana-Champaign, IL, USA, ACM, 2005:309-319.
[87]孟中楼,王殊,王骐等.大规模无线传感器网络节点部署研究[J].小型微型计算机系统, 2006, 27(11): 13-16.
[88] Jain E, Qilian L. Sensor placement and lifetime of wireless sensor networks: theory and performance analysis[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM'05)[C], 2005:5.
[89] Wang D, Xie B, Agrawal D. Coverage and lifetime optimization of wireless sensor networks with gaussian distribution [J]. IEEE Transactions on Mobile Computing, 2008, 1444-1458.
[90] Akkaya K, Younis M. Coverage and latency aware actor placement mechanisms in WSANs [J]. International Journal of Sensor Networks, 2008, 3(3): 152-164.
[91] Yuh-Ren T, Kai-Jie Y, Sz-Yi Y. Non-Uniform Node Deployment for Lifetime Extension in Large-Scale Randomly Distributed Wireless Sensor Networks[A]. Proceedings of the 22nd International Conference on Advanced Information Networking and Applications[C], Okinawa, 2008:517-524.
[92] Jian L, Mohapatra P. An analytical model for the energy hole problem in many-to-one sensor networks[A]. Proceedings of the IEEE 62nd Vehicular Technology Conference (VTC-2005-Fall)[C], 2005:2721-2725.
[93] Tarng J, Chuang B, Liu P. A relay node deployment method for disconnected wireless sensor networks: Applied in indoor environments [J]. Journal of Network and Computer Applications, 2009, 32(3): 652-659.
[94] Pandey S, Dong S, Agrawal P, et al. On performance of node placement approaches for hierarchical heterogeneous sensor networks [J]. Mobile Networks and Applications, 2009, 14(4): 401-414.
[95] Sookyoung L, Younis M. QoS-Aware Relay Node Placement in a Segmented Wireless Sensor Network[A]. Proceedings of the IEEE International Conference on Communications(ICC'09)[C], Dresden, 2009:1-5.
[96] Ibrahim a S, Seddik K G, Liu K J R. Improving Connectivity via Relays Deployment in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM'07)[C], Washington, DC, 2007:1159-1163.
[97] Hu Y, Kang Z, Shen X. An Incremental Sensor Deployment Strategy for Wireless Sensor Networks [J]. icise, 1899, 4721-4724.
[98] Kosar R, Onur E, Ersoy C. Redeployment based sensing hole mitigation in wireless sensor networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], Budapest 2009:2278-2283.
[99] Guanqun Y, Daji Q. Multi-Round Sensor Deployment for Guaranteed Barrier Coverage[A]. IEEE Proceedings INFOCOM[C], San Diego, CA 2010:1-9.
[100]温俊,蹇强,蒋杰.保证覆盖的无线传感器网络梯度部署方法[J].计算机工程与科学, 2008, 30(6): 86-90.
[101] Parikh S, Vokkarane V, Xing L, et al. Node-Replacement Policies to Maintain Threshold-Coverage in Wireless Sensor Networks[A]. Proceedings of the 16th International Conference Computer Communication Networks[C]. Honolulu, HI, 2007:760-765.
[102] Akkaya K, Younis M, Bangad M. Sink repositioning for enhanced performance in wireless sensor networks [J]. Computer Networks, 2005, 49(4): 512-534.
[103] Aitsaadi N, Achir N, Boussetta K, et al. Potential Field Approach to Ensure Connectivity and Differentiated Detection in WSN Deployment[A]. Proceedings of the IEEE International Conference on Communications( ICC'09 )[C], Dresden, 2009:1-6.
[104] Zou Y, Krishnendu C. Sensor deployment and target localization based on virtual forces[A]. Proceedings of the Twenty-Second Annual Joint Conference of the IEEE Computer and Communications[C], 2003:1293-1303.
[105] Yang X, Hui C, Kuiwu, et al. Modeling Detection Metrics in Randomized Scheduling Algorithm in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'07)[C], Kowloon, 2007:3741-3745.
[106] Wu J, Yang S. SMART: a scan-based movement-assisted sensor deployment method in wireless sensor networks[A]. Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM'05)[C], 2005:2313-2324.
[107] Wan P-J, Yi C-W. Coverage by randomly deployed wireless sensor networks [J]. IEEE/ACM Trans on Networks, 2006, 14(SI): 2658-2669.
[108] Anastasi G, Conti M, Di Francesco M, et al. Energy conservation in wireless sensor networks: A survey [J]. Ad Hoc Networks, 2009, 7(3): 537-568.
[109] Wei Y, Heidemann J, Estrin D. An energy-efficient MAC protocol for wireless sensor networks[A]. Proceedings of the Twenty-First Annual Joint Conference of the IEEE Computer andommunications Societies(INFOCOM'02)[C], 2002:1567-1576
[110] Bandyopadhyay S, Coyle E. Minimizing communication costs in hierarchically-clustered networks of wireless sensors [J]. Computer Networks, 2004, 44(1): 1-16.
[111]金岩,王玲,杨孝宗等.无线传感器网络节点调度算法及研究进展[J].宇航学报, 2007, 28(5): 1086-1093.
[112] Wang L, Xiao Y. A survey of energy-efficient scheduling mechanisms in sensor networks [J]. Mobile Networks and Applications, 2006, 11(5): 723-740.
[113] Hsin C, Liu M. Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms[A]. Proceedings of the Third International Symposium on Information Processing in Sensor Networks(IPSN'04)[C], ACM, 2004:433-442.
[114] Slijepcevic S, Potkonjak M. Power efficient organization of wireless sensor networks[A]. Proceedings of the IEEE International Conference on Communications(ICC'01)[C], Helsinki, 2001:472-476.
[115] Kumar S, Lai T H, Balogh J. On k-coverage in a mostly sleeping sensor network[A]. Proceedings of the 10th annual international conference on Mobile computing and networking[C], Philadelphia, PA, USA, ACM, 2004:144-158.
[116] Berman P, Calinescu G, Shah C, et al. Efficient energy management in sensor networks[A]. Proceedings of the Ad Hoc and Sensor Networks, ser. Wireless Networks and Mobile Computing, vol. 2, Nova Science Publishers (2005).
[117] Liu M, Cao J, Lou W, et al. Coverage Analysis for Wireless Sensor Networks [J]. Mobile Ad-hoc and Sensor Networks, 2005: 711-720.
[118] Jie J, Li F, Jun W, et al. Random Scheduling for Wireless Sensor Networks[A]. Proceedings of the 2009 IEEE International Symposium on Proceedings of the Parallel and Distributed Processing with Applications[C], Chengdu,China, 2009:324-332.
[119] Liu J, Cheung P, Zhao F, et al. A dual-space approach to tracking and sensor management in wireless sensor networks[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:131-139.
[120] Hsin C, Liu M. Randomly duty-cycled wireless sensor networks: Dynamics of coverage [J]. IEEE transactions on wireless communications, 2006, 5(11): 3182-3192.
[121]李小龙,李平,丁勇等.传感器网络中与节点位置无关的覆盖算法[J].系统仿真学报, 2009, 21(21): 6937-6841.
[122] Yan T, He T, Stankovic J A. Differentiated surveillance for sensor networks[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA, ACM, 2003:51-62.
[123] Wang B, Chua K, Srinivasan V, et al. Information coverage in randomly deployed wireless sensor networks [J]. IEEE transactions on wireless communications, 2007, 6(8): 2994-3004.
[124] Wook C, Das S K. Trade-off between coverage and data reporting latency for energy-conserving data gathering in wireless sensor networks[A]. Proceedings of the 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems[C], 2004:503-512.
[125] Shansi R, Qun L, Haining W, et al. Design and Analysis of Sensing Scheduling Algorithms under Partial Coverage for Object Detection in Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2007, 18(3): 334-350.
[126] Liu C, Wu K, King V. Randomized coverage-preserving scheduling schemes for wireless sensor networks [J]. NETWORKING, 2005, 956-967.
[127] Liu C, Wu K, Xiao Y, et al. Random coverage with guaranteed connectivity: joint scheduling for wireless sensor networks [J]. IEEE Transactions on parallel and distributed systems, 2006, 562-575.
[128] Lin J, Chen Y. Improving the coverage of randomized scheduling in wireless sensor networks [J]. IEEE transactions on wireless communications, 2008, 7(12 Part 1): 4807-4812.
[129] Yan J, Ju-Yeon J, Yoohwan K, et al. EECCP: an energy-efficient coverage- and connectivity preserving algorithm under border effects in wireless sensor networks[A]. Proceedings of the Wireless Telecommunications Symposium(WTS'08)[C], 2008:310-315.
[130] Yan J, Ling W, Ju-Yeon J, et al. EECCR: An Energy-Efficient m-Coverage and n-Connectivity Routing Algorithm Under Border Effects in Heterogeneous Sensor Networks [J]. IEEE Transactions on Vehicular Technology, 2009, 58(3): 1429-1442.
[131] Ding Y, Wang C, Xiao L. An Adaptive Partitioning Scheme for Sleep Scheduling and Topology Control in Wireless Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2009, 20(9): 1352-1365.
[132] Cerpa A, Elson J, Estrin D, et al. Habitat monitoring: Application driver for wireless communications technology [J]. ACM SIGCOMM Computer Communication Review, 2001, 31(2 supplement): 41.
[133] Deng J, Han Y, Heinzelman W, et al. Scheduling sleeping nodes in high density cluster-based sensor networks [J]. Mobile Networks and Applications, 2005, 10(6): 825-835.
[134] Deng J, Han Y, Heinzelman W, et al. Balanced-energy sleep scheduling scheme for high-density cluster-based sensor networks [J]. Computer communications, 2005, 28(14): 1631-1642.
[135] Fangyang S, Min-Te S, Chunlei L, et al. Coverage-Aware Sleep Scheduling for Cluster-Based Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], 2009:1-6.
[136] Tian D, Georganas N D. A coverage-preserving node scheduling scheme for large wireless sensor networks[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:32-41.
[137] Shen Y, Yin X, Chen H, et al. A density control algorithm for surveillance sensor networks [J]. Wireless Algorithms, Systems, and Applications, 2006, 199-205.
[138] Boukerche A, Fei X, Araujo R B. An optimal coverage-preserving scheme for wireless sensor networks based on local information exchange [J]. Computer communications, 2007, 30(14-15): 2708-2720.
[139] Jiang J, Dou W. A coverage-preserving density control algorithm for wireless sensor networks [J]. Ad-Hoc, Mobile, and Wireless Networks, 2004, 631-631.
[140] Youngtae N, Saewoom L, Kiseon K. Central Angle Decision Algorithm in Coverage-Preserving Scheme for Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'08)[C], 2008:2492-2496.
[141] Huang C-F, Tseng Y-C, Wu H-L. Distributed protocols for ensuring both coverage and connectivity of a wireless sensor network [J]. ACM Transactions on Sensor network (ToSN), 2007, 3(1): 1-24.
[142] Vinh Tran Q, Miyoshi T. An Algorithm for Sensing Coverage Problem in Wireless Sensor Networks[A]. Proceedings of the 2008 IEEE Sarnoff Symposium[C], 2008:1-5.
[143] Tian Y, Zhang S-F, Wang Y. A Distributed Protocol for Ensuring Both Probabilistic Coverage and Connectivity of High Density Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'08)[C], 2008:2069-2074.
[144] Huang C-F, Tseng Y-C. The Coverage Problem in a Wireless Sensor Network [J]. Mobile Networks and Applications, 2005, 10(4): 519-528.
[145] Chi-Fu H, Yu-Chee T, Li-Chu L. The coverage problem in three-dimensional wireless sensor networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '04)[C], 2004:3182-3186.
[146] Zhang H, Hou J. Maintaining sensing coverage and connectivity in large sensor networks [J]. Ad Hoc & Sensor Wireless Networks, 2005, 1(1-2): 89-124.
[147] Xing G, Wang X, Zhang Y, et al. Integrated coverage and connectivity configuration for energy conservation in sensor networks [J]. ACM Transactions on Sensor Networks (TOSN), 2005, 1(1): 72.
[148] Tian D, Georganas N. Connectivity maintenance and coverage preservation in wireless sensor networks [J]. Ad Hoc Networks, 2005, 3(6): 744-761.
[149] C?rbunar B, Grama A, Vitek J, et al. Redundancy and coverage detection in sensor networks [J]. ACM Transactions on Sensor network (ToSN), 2006, 2(1): 94-128.
[150] Boukerche A, Xin F. A Voronoi Approach for Coverage Protocols in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '07)[C], 2007:5190-5194.
[151] Du X, Lin F. Maintaining differentiated coverage in heterogeneous sensor networks [J]. EURASIP Journal on Wireless Communications and Networking, 2005, 2005(4): 565-572.
[152] Yan T, Gu Y, He T, et al. Design and optimization of distributed sensing coverage in wireless sensor networks [J]. ACM Transactions on Embedded Computing Systems (TECS), 2008, 7(3): 1-40.
[153] Wang L, Kulkarni S. Sacrificing a little coverage can substantially increase network lifetime [J]. Ad Hoc Networks, 2008, 6(8): 1281-1300.
[154] Bang W, Srinivasan V, Kee Chaing C, et al. Information Coverage and Network Lifetime in Energy Constrained Wireless Sensor Networks[A]. Proceedings of the 32nd IEEE Conference on Local Computer Networks(LCN)[C], 2007:512-519.
[155] Li Y, Gao S. Designing k-coverage schedules in wireless sensor networks [J]. Journal of combinatorial optimization, 2008, 15(2): 127-146.
[156] Li Y, Ai C, Cai Z, et al. Sensor scheduling for p-percent coverage in wireless sensor networks [J]. Cluster Computing, 2009: 1-14.
[157] Xu Y, Heidemann J, Estrin D. Geography-informed energy conservation for Ad Hoc routing[A]. Proceedings of the the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:70-84.
[158] Hui L, Znati T. Energy Efficient Adaptive Sensing for Dynamic Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], 2009:1-6.
[159] Shao-Feng J, Ming-Hua Y, Han-Tao S, et al. An Enhanced Perimeter Coverage Based Density Control Algorithm for Wireless Sensor Network[A]. Proceedings of the Third International Conference on Wireless and Mobile Communications(ICWMC '07)[C], IEEE Computer Society, 2007:79-79.
[160] Jun L, Suda T. Coverage-aware self-scheduling in sensor networks[A]. Proceedings of the 18th Annual Workshop on Computer Communications(CCW'03)[C], 2003:117-123.
[161] Heinzelman W, Chandrakasan A, Balakrishnan H, et al. An application-specific protocol architecture for wireless microsensor networks [J]. IEEE transactions on wireless communications, 2002, 1(4): 660-670.
[162] Hefeeda M, Ahmadi H. A Probabilistic Coverage Protocol for Wireless Sensor Networks[A]. Proceedings of the IEEE International Conference on Network Protocols(ICNP'07)[C], 2007:41-50.
[163] Hefeeda M, Ahmadi H. Energy-Efficient Protocol for Deterministic and Probabilistic Coverage in Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2010, 21(5): 579-593.
[164] Jang-Ping S, Huang-Fu L. Probabilistic Coverage Preserving Protocol with Energy Efficiency in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and NetworkingConference(WCNC'07)[C], 2007:2631-2636.
[165]石为人,袁久银,雷璐宁.无线传感器网络覆盖控制算法研究[J].自动化学报, 2009, 35(5): 540-545.
[166] Bouabdallah F, Bouabdallah N, Boutaba R. On Balancing Energy Consumption in Wireless Sensor Networks [J]. IEEE Transactions on Vehicular Technology, 2009, 58(6):
[167] Alqamzi H, Jing L. An Efficient Energy-balanced COordinated Node Scheduling (ECONS) Protocol for Dense Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '06) [C], 2006:1-5.
[168] Tran-Quang V, Miyoshi T. A novel gossip-based sensing coverage algorithm for dense wireless sensor networks [J]. Computer Networks, 2009, 53(13): 2275-2287.
[169] Stojmenovic I. Position-based routing in ad hoc networks [J]. IEEE Communications Magazine, 2002, 40(7): 128-134.
[170]石高涛,王樱锦.无线传感器网络中定位误差对覆盖控制算法的性能影响[J].计算机应用研究, 2009, 26(4): 1460-1462.
[171] Tian D, Georganas N. Location and calculation-free node-scheduling schemes in large wireless sensor networks [J]. Ad Hoc Networks, 2004, 2(1): 65-85.
[172] Gao Y, Wu K, Li F. Analysis on the redundancy of wireless sensor networks[A]. Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications[C], San Diego, CA, USA, ACM, 2003:108-114.
[173] Wu K, Gao Y, Li F, et al. Lightweight deployment-aware scheduling for wireless sensor networks [J]. Mobile Networks and Applications, 2005, 10(6): 837-852.
[174] Fan Y, Zhong G, Cheng J, et al. PEAS: a robust energy conserving protocol for long-lived sensor networks[A]. Proceedings of the 23rd International Conference on Distributed Computing Systems[C], 2003:28-37.
[175] Yen L, Cheng Y. Range-based sleep scheduling (RBSS) for wireless sensor networks [J]. Wireless Personal Communications, 2009, 48(3): 411-423.
[176]马超,史浩山,严国强等EeRCCA:一种能量有效的传感器网络覆盖控制算法[J].传感技术学报, 2009, 22(11): 1639-1644.
[177] Younis O, Krunz M, Ramasubramanian S. Location-unaware coverage in wireless sensor networks [J]. Ad Hoc Networks, 2008, 6(7): 1078-1097.
[178] Wu T-T, Ssu K-F. Determining active sensor nodes for complete coverage without location information [J]. International Journal of Ad Hoc and Ubiquitous Computing, 2005, 1(1): 38-46.
[179] Mingze Z, Mun Choon C, Ananda a L. Coverage Protocol for Wireless Sensor Networks Using Distance Estimates[A]. Proceedings of the 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks(SECON '07)[C], San Diego, CA, 2007:183-192.
[180] Saukh O, Sauter R, Gauger M, et al. On boundary recognition without location information in wireless sensor networks[A]. Proceedings of the International Conference on Information Processing in Sensor Networks(IPSN '08)[C], St. Louis, MO IEEE Computer Society, 2008:207-218.
[181] Cardei M, Du D. Improving wireless sensor network lifetime through power aware organization [J]. Wireless Networks, 2005, 11(3): 340.
[182] Yardibi T, Karasan E. A distributed activity scheduling algorithm for wireless sensor networks with partial coverage [J]. Wireless Networks (Springer), 16(1): 213-225.
[183] Boukerche A, Xin F, Araujo R B. A Coverage-Preserving and Hole Tolerant Based Scheme for the Irregular Sensing Range in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '06)[C], 2006:1-5.
[184] Xiaole B, Lei D, Jin T, et al. Directed coverage in wireless sensor networks: Concept and quality[A]. Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems(MASS '09)[C], 2009:476-485.
[185] Chen Y, Zhao Q. On the lifetime of wireless sensor networks [J]. IEEE Communications Letters, 2005, 9(11): 976-978.
[186] Falk R, Hof H J. Fighting Insomnia: A Secure Wake-Up Scheme for Wireless Sensor Networks[A]. Proceedings of the Third International Conference on Emerging Security Information, Systems and Technologies(SECURWARE '09)[C], 2009:191-196.
[187] Krysander M, Frisk E. Sensor Placement for Fault Diagnosis [J]. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 2008, 38(6): 1-1410.
[188] Shih F Y, Yi-Ta W, Jiann-Liang C. A smart sensor network for object detection, classification and recognition[A]. Proceedings of the International Conference on Wireless and Optical Communications(WOCC)[C], NJ, USA, 2005:70.
[189] Onur E, Ersoy C, Deli H. How many sensors for an acceptable breach detection probability? [J]. Computer communications, 2006, 29(2): 173-182.
[190] Hoffmann F, Kaufmann M, Kriegel K. The Art Gallery theorem for polygons with holes[A]. Proceedings of the 32nd annual symposium on Foundations of computer science[C], San Juan, Puerto Rico, IEEE Computer Society, 1991:39-48.
[191] Hall P. In Introduction to the Theory of Coverage Processes [M]. New York,NY, USA,; John Wiley & Sons Inc. 1988.
[192] Liu B, Brass P, Dousse O, et al. Mobility improves coverage of sensor networks[A]. Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing[C], Urbana-Champaign, IL, USA, ACM, 2005:300-308.
[193] Liu B, Towsley D. A study of the coverage of large-scale sensor networks[A]. Proceedings of the 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems[C], 2004:475-483.
[194] Yuh-Ren T. Sensing Coverage for Randomly Distributed Wireless Sensor Networks in Shadowed Environments [J]. IEEE Transactions on Vehicular Technology, 2008, 57(1): 556-564.
[195] Ghosh A. Estimating Coverage Holes and Enhancing Coverage in Mixed Sensor Networks[A]. Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks[C], IEEE Computer Society, 2004:68-76.
[196] Adlakha S, Srivastava M. Critical density thresholds for coverage in wireless sensor networks[A]. Proceedings of the 2003 IEEE Wireless Communications and Networking(WCNC)[C], New Orleans, 2003:1615-1620.
[197] Zou Y, Chakrabarty K. A Distributed Coverage- and Connectivity-Centric Technique for Selecting Active Nodes in Wireless Sensor Networks [J]. IEEE Transactions on Computer, 2005, 54(8): 978-991.
[198] Yun W, Xiaodong W, Bin X, et al. Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks [J]. IEEE Transactions on Mobile Computing, 2008, 7(6): 698-711.
[199] Zhang H, Hou J. On deriving the upper bound of a-lifetime for large sensor networks[A]. Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing[C], Roppongi Hills, Tokyo, Japan, ACM, 2004:121-132.
[200] Coskun V. Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks [J]. Sensors, 2008, 8(4): 2792-2817.
[201] Takahara G, Xu K, Hassanein H. How resilient is grid-based WSN coverage to deployment errors?[A]. Proceedings of the IEEE Wireless Communications & Networking Conference(WCNC'07)[C], HongKong,China, 2007:2874-2879.
[202] Yan T, He T, Stankovic J. Differentiated surveillance for sensor networks[A]. Proceedings of the ACM Int'l Conference on Embedded Networked Sensor Systems (SenSys)[C]. New York, ACM, 2003. 51-62.
[203] Choi W, Das S K. Coverage-adaptive random sensor scheduling for application-aware data gathering in wireless sensor networks [J]. Computer communications, 2006, 29(17): 3467-3482.
[204] Cao Q, Yan T, Stankovic J, et al. Analysis of target detection performance for wireless sensor networks [J]. Distributed Computing in Sensor Systems, 2005, 276-292.
[205] Qing L, Zhi T. Minimum Node Degree and k-Connectivity of a Wireless Multihop Network in Bounded Area[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '07)[C], 2007:1296-1301.
[206] Santalo L. Integral Geometry and Geometric Probability [M]. Reading, MA, USA; Addison-Wesley Publishing Company. 1976.
[207] Onur E, Ersoy C, Delic H, et al. Surveillance Wireless Sensor Networks: Deployment Quality Analysis [J]. IEEE Network, 2007, 21(6): 48-53.
[208]陶丹,孙岩,陈后金.视频传感器网络中最坏情况覆盖检测与修补算法[J].电子学报, 2009, 37(10): 2284-2290.
[209] Shih E, Cho S-H, Ickes N, et al. Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:272-287.
[210] Di Tian N. A node scheduling scheme for energy conservation in large wireless sensor networks [J]. Wireless Communications and Mobile Computing, 2003, 3(2): 271-290.
[211] Jaekyu C, Gilsoo K, Taekyoung K, et al. A Distributed Node Scheduling Protocol Considering Sensing Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE 66th Vehicular Technology Conference(VTC-2007 Fall)[C], 2007:352-356.
[212] Bejerano Y. Simple and Efficient k-Coverage Verification without Location Information[A]. Proceedings of the 27th Conference on Computer Communications(INFOCOM'08)[C], 2008: 291-295.
[213] HILL J, SZEWCZYK R, WOO A, et al. System Architecture Direc-tions for Networked Sensors [J]. ACM SIGPLAN Notices, 2000, 35(11): 93-104.
[214] YE F, ZHONG G, LU S, et al. Energy efficient robust sensing cover-age in large sensor networks. UCLA Technical Report, 2002.
[215] Hill J, Szewczyk R, Woo A, et al. System architecture directions for networked sensors [J]. Architectural Support for Programming Languages and Operating Systems, 2000, 35(11): 93-104.
[216] Brooks R R, Ramanathan P, Sayeed a M. Distributed target classification and tracking in sensor networks[A]. Proceedings of the IEEE[C], 2003:1163-1171.
[217] Aslam J, Butler Z, Constantin F, et al. Tracking a moving object with a binary sensor network[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA, ACM, 2003:150-161.
[218] He G, Hou J C. Tracking targets with quality in wireless sensor networks[A]. Proceedings of the 13th IEEE International Conference on Network Protocols(ICNP'05) [C], 2005:12-74.
[219] Ahmed N, Kanhere S S, Jha S. Probabilistic Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE Conference on Local Computer Networks 30th Anniversary[C], IEEE Computer Society, 2005:672-681.
[220] Zhou G, He T, Krishnamurthy S, et al. Impact of radio irregularity on wireless sensor networks[A]. Proceedings of the 2nd international conference on Mobile systems, applications, and services[C], Boston, MA, USA, ACM, 2004:125-138.
[221] Braem B, LatréB, Blondia C, et al. Improving Reliability in Multi-hop Body Sensor Networks[A]. Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications[C], IEEE Computer Society, 2008:342-347.
[222] T. S. Rappaport, Wireless Communications, Principles & Practice[M]. Prentice Hall, 1999.
[223] Lazos L, Poovendran R, Ritcey J A. Probabilistic detection of mobile targets in heterogeneous sensor networks[A]. Proceedings of the 6th international conference on Information processing in sensor networks[C], Cambridge, Massachusetts, USA, ACM, 2007:519-528.
[224] Kuo S-P, Tseng Y-C, Wu F-J, et al. A Probabilistic Signal-Strength-Based Evaluation Methodology for Sensor Network Deployment[A]. Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1[C], IEEE Computer Society, 2005:319-324.
[225] Clouqueur T, Saluja K K, Ramanathan P. Fault Tolerance in Collaborative Sensor Networks for Target Detection [J]. IEEE Transactions on Computers, 2004, 53(3): 320-333.
[226] Ubicell. Available from: www.wsns.net.cn.
[227] Yu C, Yen L: Tech. Rep. CHU-CSIE-TR-2003-002, Dept. CSIE, Chung Hua Univ., Taiwan, available: http://www.csie.chu.edu.tw/tech/tech_file/tech143630.pdf (July 2003), 2003.
[2]任丰原,黄海宁,林闯.无线传感器网络[J].软件学报, 2003, 14(7): 1282-1291.
[3]孙利民,李建中,陈渝等.无线传感器网络[M].北京;清华大学出版社. 2005.
[4]李建中,李金宝,石胜飞.传感器网络及其数据管理的概念、问题与进展[J].软件学报, 2003, 14(10): 1717-1727.
[5]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报, 2004, 25(4): 114-124.
[6] SmartDust. Available from: http: //robotics. eecs. berkeley. edu/~pister/SmartDust/.
[7] Simon G, Maróti M, Lédeczi, et al. Sensor network-based countersniper system[A]. Proceedings of the 2nd international conference on Embedded networked sensor systems[C], Baltimore, MD, USA, ACM, 2004:1-12.
[8] Paul J L. Smart Sensor Web: Web-based exploitation of sensor fusion for visualization of the tactical battlefield [J]. IEEE Aerospace and Electronic Systems Magazine, 2001, 16(5): 29-36.
[9] Liang S H L, Croitoru A, Tao C V. A distributed geospatial infrastructure for Sensor Web [J]. Computers & Geosciences, 2005, 31(2): 221-231.
[10] Polastre J. Design and implementation of wireless sensor networks for habitat monitoring [D]. Berkeley: University of California, 2003.
[11] Bonnet P, Gehrke J, Seshadri P. Querying the physical world [J]. IEEE Personal Communications, 2000, 7, 10-15.
[12] Tia G, Greenspan D, Welsh M, et al. Vital Signs Monitoring and Patient Tracking Over a Wireless Network[A]. Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society( EMBS)[C], 2005:102-105.
[13] SSIM. Available from: http: //www. ssim. eng. wayne. edu/.
[14] Meyer S, Rakotonirainy A. A survey of research on context-aware homes[A]. Proceedings of the Australasian information security workshop conference on ACSW frontiers [C], Adelaide, Australia, Australian Computer Society, Inc., 2003.
[15] Noury N, Herve T, Rialle V, et al. Monitoring behavior in home using a smart fall sensor and position sensors[A]. Proceedings of the 1st Annual International, Conference on Microtechnologies in Medicine and Biology[C], Lyon, France, 2000:607-610.
[16] Xu N, Rangwala S, Chintalapudi K K, et al. A wireless sensor network For structural monitoring[A]. Proceedings of the 2nd international conference on Embedded networked sensor systems[C], Baltimore, MD, USA, ACM, 2004:13-24.
[17] Coleri S, Cheung S, Varaiya P. Sensor networks for monitoring traffic[A]. Proceedings of the Allerton Conference on Communication, Control and Computing[C]. 2004:32–40.
[18] Karpiriski M, Senart A, Cahill V. Sensor networks for smart roads[A]. Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops(PerCom)[C], 2006:5-310.
[19] Callaway E H. wireless sensor networks: architectures and protocols [M]. Boca Raton Florida; CRC Press LLC. 2004.
[20] Rashid R F, Robertson G G. Accent: A communication oriented network operating system kernel [J]. SIGOPS Operating Systems Review, 1981, 15(5): 64-75.
[21] Rashid R, Julin D, Orr D, et al. Mach: a system software kernel[A]. Proceedings of the Thirty-FourthIEEE Computer Society International Conference: Intellectual Leverage, Digest of Papers[C], 1989:176-178.
[22] Myers C, Oppenheim A, Davis R, et al. Knowledge based speech analysis and enhancement[A]. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP '84)[C], 1984:162-165.
[23] Lacoss R T. Distributed Mixed Sensor Aircraft Tracking[A]. Proceedings of the American Control Conference[C], Minneapolis, MN, USA, 1987:1827-1830.
[24] D. Alberts J G, F. Stein. Network Centric Warfare, 1999. Http://Www.Dodccrp.Org/Publications/Pdf/Alberts Ncw.Pdf.
[25] SensIT. Available from: http://www.sainc.com/sensit/.
[26] ALERT System. Available from: http://www.altersystem.org/.
[27] Habitat Monitoring on Great Duck Island. Available from: http://www.greatduckisland.net.
[28] Schwiebert L, Gupta S K S, Weinmann J. Research challenges in wireless networks of biomedical sensors[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:151-165.
[29] AHRI Project. Available from: http://www.cc.gatech.edu/fce/ahri.
[30] NASA/JPL Sensor Webs Project. Available from: http://sensorwebs.jpl.nasa.gov/.
[31] EECS. Available from: http://bwrc.eecs.berkeley.edu.
[32] WEBS. Available from: http://webs.cs.berkeley.edu.
[33] CENS. Available from: http://research.cens.ucla.edu.
[34] WINS. Available from: http://www.janet.ucla.edu.
[35] NMS. Available from: http://nms.csail.mit.edu.
[36] ENALAB. Available from: http://www.eng.yale.edu/enalab.
[37] MICA. Available from: http://www/xbow.com/products/wireless_sensor_networks.htm.
[38] PicoNode. Available from: http://bwrc.eecs.berkeley.edu/research/pico_radio/default.htm.
[39] TinyOS. Available from: http://www.tinyos.net.
[40] MANTIS. Available from: http://mantis.cs.colorado.edu/index.php/tiki-index.php.
[41] SOS. Available from: http://nesl.ee.ucla.edu/projects/sos/.
[42] Meguerdichian S, Koushanfar F, Potkonjak M, et al. Coverage problems in wireless ad-hoc sensor networks[A]. Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM'01)[C], 2001:1380-1387
[43] Wang B, Wang W, Srinivasan V, et al. Information coverage for wireless sensor networks [J]. IEEE Communications Letters, 2005, 9(11): 967-969.
[44] Cardei M W J. Coverage in wireless sensor networks [M]. Ilyas M, Magboub I, eds: CRC Press, 2004.
[45] Bang W. Coverage control in sensor networks [M]. Computer Communications and Networks. 2010.
[46]任彦,张思东,张宏科.无线传感器网络中覆盖控制理论与算法[J].软件学报, 2006, 17(3): 422-433.
[47]任彦.无线传感器网络覆盖与拓扑控制理念与技术研究[D].北京:北京交通大学, 2008.
[48]蒋杰,方力,张鹤颖等.无线传感器网络最小连通覆盖集问题求解[J].软件学报, 2006, 17(2): 175-184.
[49]刘丽萍.无线传感器网络节能覆盖[D].杭州:浙江大学, 2006.
[50] Chakrabarty K, Iyengar S, Qi H, et al. Grid coverage for surveillance and target location in distributed sensor networks [J]. IEEE Transactions on Computers, 2002, 51(12): 1448-1453.
[51] Chakrabarty K, Iyengar S S, Hairong Q, et al. Coding theory framework for target location in distributed sensor networks[A]. Proceedings of the International Conference on Information Technology: Coding and Computing[C], Washington, DC, USA IEEE Computer Society2001:130-134.
[52] Zou Y. Coverage-driven sensor deployment and energy-efficient information processing in wireless sensor networks [D]: Duke University, 2004.
[53] Zou Y, Chakrabarty K. Uncertainty-aware and coverage-oriented deployment for sensor networks [J]. Journal of Parallel and Distributed Computing, 2004, 64(7): 788-798.
[54] Zou Y, Chakrabarty K. Sensor deployment and target localization in distributed sensor networks [J]. ACM Transactions on Embedded Computing Systems (TECS), 2004, 3(1): 61-91.
[55]蒋杰.无线传感器网络覆盖控制研究[D].长沙:国防科学技术大学, 2005.
[56] Veltri G, Huang Q, Qu G, et al. Minimal and maximal exposure path algorithms for wireless embedded sensor networks[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA ACM, 2003:40-50.
[57] Meguerdichian S, Koushanfar F, Qu G, et al. Exposure in wireless Ad-Hoc sensor networks[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:139-150
[58] Ma H, Liu Y. Some problems of directional sensor networks [J]. International Journal of Sensor Networks, 2007, 2(1): 44-52.
[59] Ma H, Liu Y. On coverage problems of directional sensor networks [J]. Mobile Ad-hoc and Sensor Networks, 2005, 721-731.
[60] Clouqueur T, Phipatanasuphorn V, Ramanathan P, et al. Sensor deployment strategy for detection of targets traversing a region [J]. Mobile Networks and Applications, 2003, 8(4): 453-461.
[61] Venkataraman J, Haenggi M, Collins O. Shot noise models for the dual problems of cooperative coverage and outage in random networks[A]. Proceedings of the 44th Annual Allerton Conference on Communication, Control, and Computing (Allerton)[C], Monticello, IL, 2006:1-10.
[62] Rui W, Wenming C. Universal information coverage for bandwidth-constrained sensor networks[A]. Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO)[C], Sanya, China, 2007:904-907.
[63] Xing G, Tan R, Liu B, et al. Data fusion improves the coverage of wireless sensor networks[A]. Proceedings of the 15th annual international conference on Mobile computing and networking[C], Beijing, China, ACM, 2009:157-168.
[64] Ming-Chen Z, Jiayin L, Min-You W, et al. Surface Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE INFOCOM 2009[C], 2009:109-117.
[65]张学,陆桑璐,陈贵海等.无线传感器网络的拓扑控制[J].软件学报, 2007, 18(4): 943-954.
[66] Kenan X. Device Deployment Strategies for Large-scale Wireless Sensor Networks [D]: QSpace at Queen's University, 2008.
[67] Younis O, Fahmy S. HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks [J]. IEEE Transactions on Mobile Computing, 2004, 366-379.
[68] Mhatre V, Rosenberg C, Kofman D, et al. A minimum cost heterogeneous sensor network with a lifetime constraint [J]. IEEE Transactions on Mobile Computing, 2005, 4-15.
[69] Younis M, Akkaya K. Strategies and techniques for node placement in wireless sensor networks: A survey [J]. Ad Hoc Networks, 2008, 6(4): 621-655.
[70] Romer K, Mattern F. The design space of wireless sensor networks[J]. IEEE Wireless Communications, 2004, 11(6): 54-61.
[71] O’rourke J. Art Gallery Theorems and Algorithms. The International Series of Monographs on Computer Science [M]. Oxford University Press, New York, NY. 1987.
[72] Shakkottai S, Srikant R, Shroff N. Unreliable sensor grids: Coverage, connectivity and diameter [J]. Ad Hoc Networks, 2005, 3(6): 702-716.
[73] Coskun V. Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks [J]. Sensors, 2008, 8, 2792-2817.
[74]王晓东.无线传感器网络节能算法研究[D].杭州:浙江大学, 2007.
[75] Tilak S, Abu-Ghazaleh NB, Heinzelman W. Infrastructure trade-offs for sensor networks. Proceedings of First InternationalWorkshop on Wireless Sensor Networks and Applications (WSNA'02), 2002: 49-57.
[76] Balister P, Bollobas B, Sarkar A, et al. Reliable density estimates for coverage and connectivity in thin strips of finite length[A]. Proceedings of the 13th annual ACM international conference on Mobile computing and networking [C], Montréal, Québec, Canada, ACM, 2007:75-86.
[77] González-Banos H. A randomized art-gallery algorithm for sensor placement [M]. Proceedings of the seventeenth annual symposium on Computational geometry. Medford, Massachusetts, United States, ACM. 2001: 232-240.
[78] Zhang H, Hou J C. Is Deterministic Deployment Worse than Random Deployment for Wireless Sensor Networks?[A]. Proceedings of the 25th IEEE International Conference on Computer Communications[C], Barcelona, Spain, 2006:1-13.
[79] Onur E, Ersoy C, Delic H. How many sensors for an acceptable breach detection probability? [J]. Computer communications, 2006, 29(2): 173-182.
[80] Balister P, Kumar S. Random vs. Deterministic Deployment of Sensors in the Presence of Failures and Placement Errors[A]. Proceedings of the IEEE INFOCOM 2009[C], 2009:2896-2900.
[81] Leoncini M, Resta G, Santi P. Partially controlled deployment strategies for wireless sensors [J]. Ad Hoc Networks, 2009, 7(1): 1-23.
[82] Leow W L, Pishro-Nik H. Results on coverage for finite wireless networks[A]. Proceedings of the 2007 international conference on Wireless communications and mobile computing[C], Honolulu, Hawaii, USA, ACM, 2007:364-369
[83] Clouqueur T, Phipatanasuphorn V, Ramanathan P, et al. Sensor deployment strategy for target detection[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:42-48.
[84] Hou Y, Chen C, Jeng B. An optimal new-node placement to enhance the coverage of wireless sensor networks [J]. Wireless Networks, 16(4): 1033-1043.
[85]刘明,曹建农,郑源等.无线传感器网络多重覆盖问题分析[J].软件学报, 2007, 28(1): 125-136.
[86] Bredin J L, Demaine E D, Hajiaghayi M, et al. Deploying sensor networks with guaranteed capacity and fault tolerance[A]. Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing[C], Urbana-Champaign, IL, USA, ACM, 2005:309-319.
[87]孟中楼,王殊,王骐等.大规模无线传感器网络节点部署研究[J].小型微型计算机系统, 2006, 27(11): 13-16.
[88] Jain E, Qilian L. Sensor placement and lifetime of wireless sensor networks: theory and performance analysis[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM'05)[C], 2005:5.
[89] Wang D, Xie B, Agrawal D. Coverage and lifetime optimization of wireless sensor networks with gaussian distribution [J]. IEEE Transactions on Mobile Computing, 2008, 1444-1458.
[90] Akkaya K, Younis M. Coverage and latency aware actor placement mechanisms in WSANs [J]. International Journal of Sensor Networks, 2008, 3(3): 152-164.
[91] Yuh-Ren T, Kai-Jie Y, Sz-Yi Y. Non-Uniform Node Deployment for Lifetime Extension in Large-Scale Randomly Distributed Wireless Sensor Networks[A]. Proceedings of the 22nd International Conference on Advanced Information Networking and Applications[C], Okinawa, 2008:517-524.
[92] Jian L, Mohapatra P. An analytical model for the energy hole problem in many-to-one sensor networks[A]. Proceedings of the IEEE 62nd Vehicular Technology Conference (VTC-2005-Fall)[C], 2005:2721-2725.
[93] Tarng J, Chuang B, Liu P. A relay node deployment method for disconnected wireless sensor networks: Applied in indoor environments [J]. Journal of Network and Computer Applications, 2009, 32(3): 652-659.
[94] Pandey S, Dong S, Agrawal P, et al. On performance of node placement approaches for hierarchical heterogeneous sensor networks [J]. Mobile Networks and Applications, 2009, 14(4): 401-414.
[95] Sookyoung L, Younis M. QoS-Aware Relay Node Placement in a Segmented Wireless Sensor Network[A]. Proceedings of the IEEE International Conference on Communications(ICC'09)[C], Dresden, 2009:1-5.
[96] Ibrahim a S, Seddik K G, Liu K J R. Improving Connectivity via Relays Deployment in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM'07)[C], Washington, DC, 2007:1159-1163.
[97] Hu Y, Kang Z, Shen X. An Incremental Sensor Deployment Strategy for Wireless Sensor Networks [J]. icise, 1899, 4721-4724.
[98] Kosar R, Onur E, Ersoy C. Redeployment based sensing hole mitigation in wireless sensor networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], Budapest 2009:2278-2283.
[99] Guanqun Y, Daji Q. Multi-Round Sensor Deployment for Guaranteed Barrier Coverage[A]. IEEE Proceedings INFOCOM[C], San Diego, CA 2010:1-9.
[100]温俊,蹇强,蒋杰.保证覆盖的无线传感器网络梯度部署方法[J].计算机工程与科学, 2008, 30(6): 86-90.
[101] Parikh S, Vokkarane V, Xing L, et al. Node-Replacement Policies to Maintain Threshold-Coverage in Wireless Sensor Networks[A]. Proceedings of the 16th International Conference Computer Communication Networks[C]. Honolulu, HI, 2007:760-765.
[102] Akkaya K, Younis M, Bangad M. Sink repositioning for enhanced performance in wireless sensor networks [J]. Computer Networks, 2005, 49(4): 512-534.
[103] Aitsaadi N, Achir N, Boussetta K, et al. Potential Field Approach to Ensure Connectivity and Differentiated Detection in WSN Deployment[A]. Proceedings of the IEEE International Conference on Communications( ICC'09 )[C], Dresden, 2009:1-6.
[104] Zou Y, Krishnendu C. Sensor deployment and target localization based on virtual forces[A]. Proceedings of the Twenty-Second Annual Joint Conference of the IEEE Computer and Communications[C], 2003:1293-1303.
[105] Yang X, Hui C, Kuiwu, et al. Modeling Detection Metrics in Randomized Scheduling Algorithm in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'07)[C], Kowloon, 2007:3741-3745.
[106] Wu J, Yang S. SMART: a scan-based movement-assisted sensor deployment method in wireless sensor networks[A]. Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies(INFOCOM'05)[C], 2005:2313-2324.
[107] Wan P-J, Yi C-W. Coverage by randomly deployed wireless sensor networks [J]. IEEE/ACM Trans on Networks, 2006, 14(SI): 2658-2669.
[108] Anastasi G, Conti M, Di Francesco M, et al. Energy conservation in wireless sensor networks: A survey [J]. Ad Hoc Networks, 2009, 7(3): 537-568.
[109] Wei Y, Heidemann J, Estrin D. An energy-efficient MAC protocol for wireless sensor networks[A]. Proceedings of the Twenty-First Annual Joint Conference of the IEEE Computer andommunications Societies(INFOCOM'02)[C], 2002:1567-1576
[110] Bandyopadhyay S, Coyle E. Minimizing communication costs in hierarchically-clustered networks of wireless sensors [J]. Computer Networks, 2004, 44(1): 1-16.
[111]金岩,王玲,杨孝宗等.无线传感器网络节点调度算法及研究进展[J].宇航学报, 2007, 28(5): 1086-1093.
[112] Wang L, Xiao Y. A survey of energy-efficient scheduling mechanisms in sensor networks [J]. Mobile Networks and Applications, 2006, 11(5): 723-740.
[113] Hsin C, Liu M. Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms[A]. Proceedings of the Third International Symposium on Information Processing in Sensor Networks(IPSN'04)[C], ACM, 2004:433-442.
[114] Slijepcevic S, Potkonjak M. Power efficient organization of wireless sensor networks[A]. Proceedings of the IEEE International Conference on Communications(ICC'01)[C], Helsinki, 2001:472-476.
[115] Kumar S, Lai T H, Balogh J. On k-coverage in a mostly sleeping sensor network[A]. Proceedings of the 10th annual international conference on Mobile computing and networking[C], Philadelphia, PA, USA, ACM, 2004:144-158.
[116] Berman P, Calinescu G, Shah C, et al. Efficient energy management in sensor networks[A]. Proceedings of the Ad Hoc and Sensor Networks, ser. Wireless Networks and Mobile Computing, vol. 2, Nova Science Publishers (2005).
[117] Liu M, Cao J, Lou W, et al. Coverage Analysis for Wireless Sensor Networks [J]. Mobile Ad-hoc and Sensor Networks, 2005: 711-720.
[118] Jie J, Li F, Jun W, et al. Random Scheduling for Wireless Sensor Networks[A]. Proceedings of the 2009 IEEE International Symposium on Proceedings of the Parallel and Distributed Processing with Applications[C], Chengdu,China, 2009:324-332.
[119] Liu J, Cheung P, Zhao F, et al. A dual-space approach to tracking and sensor management in wireless sensor networks[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:131-139.
[120] Hsin C, Liu M. Randomly duty-cycled wireless sensor networks: Dynamics of coverage [J]. IEEE transactions on wireless communications, 2006, 5(11): 3182-3192.
[121]李小龙,李平,丁勇等.传感器网络中与节点位置无关的覆盖算法[J].系统仿真学报, 2009, 21(21): 6937-6841.
[122] Yan T, He T, Stankovic J A. Differentiated surveillance for sensor networks[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA, ACM, 2003:51-62.
[123] Wang B, Chua K, Srinivasan V, et al. Information coverage in randomly deployed wireless sensor networks [J]. IEEE transactions on wireless communications, 2007, 6(8): 2994-3004.
[124] Wook C, Das S K. Trade-off between coverage and data reporting latency for energy-conserving data gathering in wireless sensor networks[A]. Proceedings of the 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems[C], 2004:503-512.
[125] Shansi R, Qun L, Haining W, et al. Design and Analysis of Sensing Scheduling Algorithms under Partial Coverage for Object Detection in Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2007, 18(3): 334-350.
[126] Liu C, Wu K, King V. Randomized coverage-preserving scheduling schemes for wireless sensor networks [J]. NETWORKING, 2005, 956-967.
[127] Liu C, Wu K, Xiao Y, et al. Random coverage with guaranteed connectivity: joint scheduling for wireless sensor networks [J]. IEEE Transactions on parallel and distributed systems, 2006, 562-575.
[128] Lin J, Chen Y. Improving the coverage of randomized scheduling in wireless sensor networks [J]. IEEE transactions on wireless communications, 2008, 7(12 Part 1): 4807-4812.
[129] Yan J, Ju-Yeon J, Yoohwan K, et al. EECCP: an energy-efficient coverage- and connectivity preserving algorithm under border effects in wireless sensor networks[A]. Proceedings of the Wireless Telecommunications Symposium(WTS'08)[C], 2008:310-315.
[130] Yan J, Ling W, Ju-Yeon J, et al. EECCR: An Energy-Efficient m-Coverage and n-Connectivity Routing Algorithm Under Border Effects in Heterogeneous Sensor Networks [J]. IEEE Transactions on Vehicular Technology, 2009, 58(3): 1429-1442.
[131] Ding Y, Wang C, Xiao L. An Adaptive Partitioning Scheme for Sleep Scheduling and Topology Control in Wireless Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2009, 20(9): 1352-1365.
[132] Cerpa A, Elson J, Estrin D, et al. Habitat monitoring: Application driver for wireless communications technology [J]. ACM SIGCOMM Computer Communication Review, 2001, 31(2 supplement): 41.
[133] Deng J, Han Y, Heinzelman W, et al. Scheduling sleeping nodes in high density cluster-based sensor networks [J]. Mobile Networks and Applications, 2005, 10(6): 825-835.
[134] Deng J, Han Y, Heinzelman W, et al. Balanced-energy sleep scheduling scheme for high-density cluster-based sensor networks [J]. Computer communications, 2005, 28(14): 1631-1642.
[135] Fangyang S, Min-Te S, Chunlei L, et al. Coverage-Aware Sleep Scheduling for Cluster-Based Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], 2009:1-6.
[136] Tian D, Georganas N D. A coverage-preserving node scheduling scheme for large wireless sensor networks[A]. Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications[C], Atlanta, Georgia, USA, ACM, 2002:32-41.
[137] Shen Y, Yin X, Chen H, et al. A density control algorithm for surveillance sensor networks [J]. Wireless Algorithms, Systems, and Applications, 2006, 199-205.
[138] Boukerche A, Fei X, Araujo R B. An optimal coverage-preserving scheme for wireless sensor networks based on local information exchange [J]. Computer communications, 2007, 30(14-15): 2708-2720.
[139] Jiang J, Dou W. A coverage-preserving density control algorithm for wireless sensor networks [J]. Ad-Hoc, Mobile, and Wireless Networks, 2004, 631-631.
[140] Youngtae N, Saewoom L, Kiseon K. Central Angle Decision Algorithm in Coverage-Preserving Scheme for Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'08)[C], 2008:2492-2496.
[141] Huang C-F, Tseng Y-C, Wu H-L. Distributed protocols for ensuring both coverage and connectivity of a wireless sensor network [J]. ACM Transactions on Sensor network (ToSN), 2007, 3(1): 1-24.
[142] Vinh Tran Q, Miyoshi T. An Algorithm for Sensing Coverage Problem in Wireless Sensor Networks[A]. Proceedings of the 2008 IEEE Sarnoff Symposium[C], 2008:1-5.
[143] Tian Y, Zhang S-F, Wang Y. A Distributed Protocol for Ensuring Both Probabilistic Coverage and Connectivity of High Density Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'08)[C], 2008:2069-2074.
[144] Huang C-F, Tseng Y-C. The Coverage Problem in a Wireless Sensor Network [J]. Mobile Networks and Applications, 2005, 10(4): 519-528.
[145] Chi-Fu H, Yu-Chee T, Li-Chu L. The coverage problem in three-dimensional wireless sensor networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '04)[C], 2004:3182-3186.
[146] Zhang H, Hou J. Maintaining sensing coverage and connectivity in large sensor networks [J]. Ad Hoc & Sensor Wireless Networks, 2005, 1(1-2): 89-124.
[147] Xing G, Wang X, Zhang Y, et al. Integrated coverage and connectivity configuration for energy conservation in sensor networks [J]. ACM Transactions on Sensor Networks (TOSN), 2005, 1(1): 72.
[148] Tian D, Georganas N. Connectivity maintenance and coverage preservation in wireless sensor networks [J]. Ad Hoc Networks, 2005, 3(6): 744-761.
[149] C?rbunar B, Grama A, Vitek J, et al. Redundancy and coverage detection in sensor networks [J]. ACM Transactions on Sensor network (ToSN), 2006, 2(1): 94-128.
[150] Boukerche A, Xin F. A Voronoi Approach for Coverage Protocols in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '07)[C], 2007:5190-5194.
[151] Du X, Lin F. Maintaining differentiated coverage in heterogeneous sensor networks [J]. EURASIP Journal on Wireless Communications and Networking, 2005, 2005(4): 565-572.
[152] Yan T, Gu Y, He T, et al. Design and optimization of distributed sensing coverage in wireless sensor networks [J]. ACM Transactions on Embedded Computing Systems (TECS), 2008, 7(3): 1-40.
[153] Wang L, Kulkarni S. Sacrificing a little coverage can substantially increase network lifetime [J]. Ad Hoc Networks, 2008, 6(8): 1281-1300.
[154] Bang W, Srinivasan V, Kee Chaing C, et al. Information Coverage and Network Lifetime in Energy Constrained Wireless Sensor Networks[A]. Proceedings of the 32nd IEEE Conference on Local Computer Networks(LCN)[C], 2007:512-519.
[155] Li Y, Gao S. Designing k-coverage schedules in wireless sensor networks [J]. Journal of combinatorial optimization, 2008, 15(2): 127-146.
[156] Li Y, Ai C, Cai Z, et al. Sensor scheduling for p-percent coverage in wireless sensor networks [J]. Cluster Computing, 2009: 1-14.
[157] Xu Y, Heidemann J, Estrin D. Geography-informed energy conservation for Ad Hoc routing[A]. Proceedings of the the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:70-84.
[158] Hui L, Znati T. Energy Efficient Adaptive Sensing for Dynamic Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and Networking Conference(WCNC'09)[C], 2009:1-6.
[159] Shao-Feng J, Ming-Hua Y, Han-Tao S, et al. An Enhanced Perimeter Coverage Based Density Control Algorithm for Wireless Sensor Network[A]. Proceedings of the Third International Conference on Wireless and Mobile Communications(ICWMC '07)[C], IEEE Computer Society, 2007:79-79.
[160] Jun L, Suda T. Coverage-aware self-scheduling in sensor networks[A]. Proceedings of the 18th Annual Workshop on Computer Communications(CCW'03)[C], 2003:117-123.
[161] Heinzelman W, Chandrakasan A, Balakrishnan H, et al. An application-specific protocol architecture for wireless microsensor networks [J]. IEEE transactions on wireless communications, 2002, 1(4): 660-670.
[162] Hefeeda M, Ahmadi H. A Probabilistic Coverage Protocol for Wireless Sensor Networks[A]. Proceedings of the IEEE International Conference on Network Protocols(ICNP'07)[C], 2007:41-50.
[163] Hefeeda M, Ahmadi H. Energy-Efficient Protocol for Deterministic and Probabilistic Coverage in Sensor Networks [J]. IEEE Transactions on parallel and distributed systems, 2010, 21(5): 579-593.
[164] Jang-Ping S, Huang-Fu L. Probabilistic Coverage Preserving Protocol with Energy Efficiency in Wireless Sensor Networks[A]. Proceedings of the IEEE Wireless Communications and NetworkingConference(WCNC'07)[C], 2007:2631-2636.
[165]石为人,袁久银,雷璐宁.无线传感器网络覆盖控制算法研究[J].自动化学报, 2009, 35(5): 540-545.
[166] Bouabdallah F, Bouabdallah N, Boutaba R. On Balancing Energy Consumption in Wireless Sensor Networks [J]. IEEE Transactions on Vehicular Technology, 2009, 58(6):
[167] Alqamzi H, Jing L. An Efficient Energy-balanced COordinated Node Scheduling (ECONS) Protocol for Dense Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '06) [C], 2006:1-5.
[168] Tran-Quang V, Miyoshi T. A novel gossip-based sensing coverage algorithm for dense wireless sensor networks [J]. Computer Networks, 2009, 53(13): 2275-2287.
[169] Stojmenovic I. Position-based routing in ad hoc networks [J]. IEEE Communications Magazine, 2002, 40(7): 128-134.
[170]石高涛,王樱锦.无线传感器网络中定位误差对覆盖控制算法的性能影响[J].计算机应用研究, 2009, 26(4): 1460-1462.
[171] Tian D, Georganas N. Location and calculation-free node-scheduling schemes in large wireless sensor networks [J]. Ad Hoc Networks, 2004, 2(1): 65-85.
[172] Gao Y, Wu K, Li F. Analysis on the redundancy of wireless sensor networks[A]. Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications[C], San Diego, CA, USA, ACM, 2003:108-114.
[173] Wu K, Gao Y, Li F, et al. Lightweight deployment-aware scheduling for wireless sensor networks [J]. Mobile Networks and Applications, 2005, 10(6): 837-852.
[174] Fan Y, Zhong G, Cheng J, et al. PEAS: a robust energy conserving protocol for long-lived sensor networks[A]. Proceedings of the 23rd International Conference on Distributed Computing Systems[C], 2003:28-37.
[175] Yen L, Cheng Y. Range-based sleep scheduling (RBSS) for wireless sensor networks [J]. Wireless Personal Communications, 2009, 48(3): 411-423.
[176]马超,史浩山,严国强等EeRCCA:一种能量有效的传感器网络覆盖控制算法[J].传感技术学报, 2009, 22(11): 1639-1644.
[177] Younis O, Krunz M, Ramasubramanian S. Location-unaware coverage in wireless sensor networks [J]. Ad Hoc Networks, 2008, 6(7): 1078-1097.
[178] Wu T-T, Ssu K-F. Determining active sensor nodes for complete coverage without location information [J]. International Journal of Ad Hoc and Ubiquitous Computing, 2005, 1(1): 38-46.
[179] Mingze Z, Mun Choon C, Ananda a L. Coverage Protocol for Wireless Sensor Networks Using Distance Estimates[A]. Proceedings of the 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks(SECON '07)[C], San Diego, CA, 2007:183-192.
[180] Saukh O, Sauter R, Gauger M, et al. On boundary recognition without location information in wireless sensor networks[A]. Proceedings of the International Conference on Information Processing in Sensor Networks(IPSN '08)[C], St. Louis, MO IEEE Computer Society, 2008:207-218.
[181] Cardei M, Du D. Improving wireless sensor network lifetime through power aware organization [J]. Wireless Networks, 2005, 11(3): 340.
[182] Yardibi T, Karasan E. A distributed activity scheduling algorithm for wireless sensor networks with partial coverage [J]. Wireless Networks (Springer), 16(1): 213-225.
[183] Boukerche A, Xin F, Araujo R B. A Coverage-Preserving and Hole Tolerant Based Scheme for the Irregular Sensing Range in Wireless Sensor Networks[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '06)[C], 2006:1-5.
[184] Xiaole B, Lei D, Jin T, et al. Directed coverage in wireless sensor networks: Concept and quality[A]. Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems(MASS '09)[C], 2009:476-485.
[185] Chen Y, Zhao Q. On the lifetime of wireless sensor networks [J]. IEEE Communications Letters, 2005, 9(11): 976-978.
[186] Falk R, Hof H J. Fighting Insomnia: A Secure Wake-Up Scheme for Wireless Sensor Networks[A]. Proceedings of the Third International Conference on Emerging Security Information, Systems and Technologies(SECURWARE '09)[C], 2009:191-196.
[187] Krysander M, Frisk E. Sensor Placement for Fault Diagnosis [J]. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 2008, 38(6): 1-1410.
[188] Shih F Y, Yi-Ta W, Jiann-Liang C. A smart sensor network for object detection, classification and recognition[A]. Proceedings of the International Conference on Wireless and Optical Communications(WOCC)[C], NJ, USA, 2005:70.
[189] Onur E, Ersoy C, Deli H. How many sensors for an acceptable breach detection probability? [J]. Computer communications, 2006, 29(2): 173-182.
[190] Hoffmann F, Kaufmann M, Kriegel K. The Art Gallery theorem for polygons with holes[A]. Proceedings of the 32nd annual symposium on Foundations of computer science[C], San Juan, Puerto Rico, IEEE Computer Society, 1991:39-48.
[191] Hall P. In Introduction to the Theory of Coverage Processes [M]. New York,NY, USA,; John Wiley & Sons Inc. 1988.
[192] Liu B, Brass P, Dousse O, et al. Mobility improves coverage of sensor networks[A]. Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing[C], Urbana-Champaign, IL, USA, ACM, 2005:300-308.
[193] Liu B, Towsley D. A study of the coverage of large-scale sensor networks[A]. Proceedings of the 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems[C], 2004:475-483.
[194] Yuh-Ren T. Sensing Coverage for Randomly Distributed Wireless Sensor Networks in Shadowed Environments [J]. IEEE Transactions on Vehicular Technology, 2008, 57(1): 556-564.
[195] Ghosh A. Estimating Coverage Holes and Enhancing Coverage in Mixed Sensor Networks[A]. Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks[C], IEEE Computer Society, 2004:68-76.
[196] Adlakha S, Srivastava M. Critical density thresholds for coverage in wireless sensor networks[A]. Proceedings of the 2003 IEEE Wireless Communications and Networking(WCNC)[C], New Orleans, 2003:1615-1620.
[197] Zou Y, Chakrabarty K. A Distributed Coverage- and Connectivity-Centric Technique for Selecting Active Nodes in Wireless Sensor Networks [J]. IEEE Transactions on Computer, 2005, 54(8): 978-991.
[198] Yun W, Xiaodong W, Bin X, et al. Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks [J]. IEEE Transactions on Mobile Computing, 2008, 7(6): 698-711.
[199] Zhang H, Hou J. On deriving the upper bound of a-lifetime for large sensor networks[A]. Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing[C], Roppongi Hills, Tokyo, Japan, ACM, 2004:121-132.
[200] Coskun V. Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks [J]. Sensors, 2008, 8(4): 2792-2817.
[201] Takahara G, Xu K, Hassanein H. How resilient is grid-based WSN coverage to deployment errors?[A]. Proceedings of the IEEE Wireless Communications & Networking Conference(WCNC'07)[C], HongKong,China, 2007:2874-2879.
[202] Yan T, He T, Stankovic J. Differentiated surveillance for sensor networks[A]. Proceedings of the ACM Int'l Conference on Embedded Networked Sensor Systems (SenSys)[C]. New York, ACM, 2003. 51-62.
[203] Choi W, Das S K. Coverage-adaptive random sensor scheduling for application-aware data gathering in wireless sensor networks [J]. Computer communications, 2006, 29(17): 3467-3482.
[204] Cao Q, Yan T, Stankovic J, et al. Analysis of target detection performance for wireless sensor networks [J]. Distributed Computing in Sensor Systems, 2005, 276-292.
[205] Qing L, Zhi T. Minimum Node Degree and k-Connectivity of a Wireless Multihop Network in Bounded Area[A]. Proceedings of the IEEE Global Telecommunications Conference(GLOBECOM '07)[C], 2007:1296-1301.
[206] Santalo L. Integral Geometry and Geometric Probability [M]. Reading, MA, USA; Addison-Wesley Publishing Company. 1976.
[207] Onur E, Ersoy C, Delic H, et al. Surveillance Wireless Sensor Networks: Deployment Quality Analysis [J]. IEEE Network, 2007, 21(6): 48-53.
[208]陶丹,孙岩,陈后金.视频传感器网络中最坏情况覆盖检测与修补算法[J].电子学报, 2009, 37(10): 2284-2290.
[209] Shih E, Cho S-H, Ickes N, et al. Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks[A]. Proceedings of the 7th annual international conference on Mobile computing and networking[C], Rome, Italy, ACM, 2001:272-287.
[210] Di Tian N. A node scheduling scheme for energy conservation in large wireless sensor networks [J]. Wireless Communications and Mobile Computing, 2003, 3(2): 271-290.
[211] Jaekyu C, Gilsoo K, Taekyoung K, et al. A Distributed Node Scheduling Protocol Considering Sensing Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE 66th Vehicular Technology Conference(VTC-2007 Fall)[C], 2007:352-356.
[212] Bejerano Y. Simple and Efficient k-Coverage Verification without Location Information[A]. Proceedings of the 27th Conference on Computer Communications(INFOCOM'08)[C], 2008: 291-295.
[213] HILL J, SZEWCZYK R, WOO A, et al. System Architecture Direc-tions for Networked Sensors [J]. ACM SIGPLAN Notices, 2000, 35(11): 93-104.
[214] YE F, ZHONG G, LU S, et al. Energy efficient robust sensing cover-age in large sensor networks. UCLA Technical Report, 2002.
[215] Hill J, Szewczyk R, Woo A, et al. System architecture directions for networked sensors [J]. Architectural Support for Programming Languages and Operating Systems, 2000, 35(11): 93-104.
[216] Brooks R R, Ramanathan P, Sayeed a M. Distributed target classification and tracking in sensor networks[A]. Proceedings of the IEEE[C], 2003:1163-1171.
[217] Aslam J, Butler Z, Constantin F, et al. Tracking a moving object with a binary sensor network[A]. Proceedings of the 1st international conference on Embedded networked sensor systems[C], Los Angeles, California, USA, ACM, 2003:150-161.
[218] He G, Hou J C. Tracking targets with quality in wireless sensor networks[A]. Proceedings of the 13th IEEE International Conference on Network Protocols(ICNP'05) [C], 2005:12-74.
[219] Ahmed N, Kanhere S S, Jha S. Probabilistic Coverage in Wireless Sensor Networks[A]. Proceedings of the IEEE Conference on Local Computer Networks 30th Anniversary[C], IEEE Computer Society, 2005:672-681.
[220] Zhou G, He T, Krishnamurthy S, et al. Impact of radio irregularity on wireless sensor networks[A]. Proceedings of the 2nd international conference on Mobile systems, applications, and services[C], Boston, MA, USA, ACM, 2004:125-138.
[221] Braem B, LatréB, Blondia C, et al. Improving Reliability in Multi-hop Body Sensor Networks[A]. Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications[C], IEEE Computer Society, 2008:342-347.
[222] T. S. Rappaport, Wireless Communications, Principles & Practice[M]. Prentice Hall, 1999.
[223] Lazos L, Poovendran R, Ritcey J A. Probabilistic detection of mobile targets in heterogeneous sensor networks[A]. Proceedings of the 6th international conference on Information processing in sensor networks[C], Cambridge, Massachusetts, USA, ACM, 2007:519-528.
[224] Kuo S-P, Tseng Y-C, Wu F-J, et al. A Probabilistic Signal-Strength-Based Evaluation Methodology for Sensor Network Deployment[A]. Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1[C], IEEE Computer Society, 2005:319-324.
[225] Clouqueur T, Saluja K K, Ramanathan P. Fault Tolerance in Collaborative Sensor Networks for Target Detection [J]. IEEE Transactions on Computers, 2004, 53(3): 320-333.
[226] Ubicell. Available from: www.wsns.net.cn.
[227] Yu C, Yen L: Tech. Rep. CHU-CSIE-TR-2003-002, Dept. CSIE, Chung Hua Univ., Taiwan, available: http://www.csie.chu.edu.tw/tech/tech_file/tech143630.pdf (July 2003), 2003.