ERC~2:具有拥塞控制策略的DTN传染路由方法
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摘要
针对延迟容忍网络(DTN)拓扑结构动态变化和节点存储空间有限的问题,提出一种具有拥塞控制策略的DTN传染路由(ERC~2)方法。该方法基于一种动态存储状态模型(DSSM),节点可通过感知网络状况动态调整节点半拥塞状态的门限降低网络发生拥塞的可能性,增加ACK索引以及消息管理队列,使节点存储状态随着网络负载的随机变化而动态更新并主动删除冗余包,并根据不同拥塞状态结合传染路由和Prophet路由的优点选择单一或混合模式进行消息转发,从而达到预防、避免、解除拥塞的目的,实现节点自适应缓存管理以及网络的动态拥塞控制。在模拟器ONE上采用Working Day Movement模型进行仿真,其中与Prophet相比,ERC~2方法在消息递交率上提高66. 18%,平均时延降低48. 36%,转发次数提高22. 83%。仿真结果表明,在拥塞程度不同的场景中,ERC~2与Epidemic、Prophet路由算法相比具有更好的网络性能。
Delay Tolerant Network( DTN) has characteristics of dynamic topology changes and limited node storage space. A DTN Epidemic Routing with Congestion Control strategy( ERC~2) method was proposed. The method was based on a Dynamic Storage State Model( DSSM). According to sensing network conditions, the threshold of node's semi-congested state was dynamically adjusted to reduce the possibility of network congestion by nodes. The ACK index and message management queue were added to make node storage state change randomly with network load, dynamically update and actively delete redundant packages. Single or mixed mode was selected for message forwarding according to different congestion states combining with advantages of Epidemic and Prophet routing, so as to achieve the purpose of preventing, avoiding and canceling congestion, realizing adaptive buffer management of nodes and dynamically controlling congestion of network.Simulations were conducted on the ONE( Opportunistic Networking Environment) platform using Working Day Movement( WDM) model. In the simulation, ERC~2 was 66. 18% higher than Prophet in message delivery rate. The average latency of ERC~2 was decreased by 48. 36%, and the forwarding number was increased by 22. 83%. The simulation results show that ERC~2 has better network performance than Epidemic and Prophet routing algorithms in scenarios with different levels of congestion.
Delay Tolerant Network( DTN) has characteristics of dynamic topology changes and limited node storage space. A DTN Epidemic Routing with Congestion Control strategy( ERC~2) method was proposed. The method was based on a Dynamic Storage State Model( DSSM). According to sensing network conditions, the threshold of node's semi-congested state was dynamically adjusted to reduce the possibility of network congestion by nodes. The ACK index and message management queue were added to make node storage state change randomly with network load, dynamically update and actively delete redundant packages. Single or mixed mode was selected for message forwarding according to different congestion states combining with advantages of Epidemic and Prophet routing, so as to achieve the purpose of preventing, avoiding and canceling congestion, realizing adaptive buffer management of nodes and dynamically controlling congestion of network.Simulations were conducted on the ONE( Opportunistic Networking Environment) platform using Working Day Movement( WDM) model. In the simulation, ERC~2 was 66. 18% higher than Prophet in message delivery rate. The average latency of ERC~2 was decreased by 48. 36%, and the forwarding number was increased by 22. 83%. The simulation results show that ERC~2 has better network performance than Epidemic and Prophet routing algorithms in scenarios with different levels of congestion.
引文
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[2]王挺,张玉梅.一种基于DTN的震后救援路由新策略[J].计算机工程与应用,2017,53(22):71-76.(WANG T, ZHANG Y M.Routing strategy for post earthquake rescue based on DTN[J]. Computer Engineering and Applications, 2017, 53(22):71-76.)
[3]王贺哲,王慧强,朱金美,等. OCIGM:面向DTN路由的优化控制信息生成方法[J].北京邮电大学学报,2017,40(1):79-83.(WANG H Z, WANG H Q, ZHU J M, et al. OCIGM:an optimized control information generation method for DTN routing[J]. Journal of Beijing University of Posts and Telecommunications, 2017, 40(1):79-83.)
[4]SIDERA A, TOUMPIS S. Wireless mobile DTN routing with the extended minimum estimated expected delay protocol[J]. Ad Hoc Networks, 2016, 42(C):47-60.
[5]王恩,杨永健,李莅.基于动态半马尔可夫路径搜索模型的DTN分簇路由方法[J].计算机学报,2015,38(3):483-499.(WANG E, YANG Y J, LI L. A clustering routing method based on semiMarkov process and path-finding strategy in DTN[J]. Chinese Journal of Computers, 2015, 38(3):483-499.)
[6]曹玖新,陈高君,杨婧,等.基于社会属性的PSN消息路由算法[J].通信学报,2015,36(5):13-22.(CAO J X, CHEN G J,YANG J, et al. Social-based routing in pocket switched networks[J]. Journal on Communications, 2015, 36(5):13-22.)
[7]ZHANG L, CAI Z, LU J, et al. Mobility-aware routing in delay tolerant networks[J]. Personal&Ubiquitous Computing, 2015, 19(7):1-13.
[8]NISHIYAMA H, TAKAHASHI A, KATO N, et al. Dynamic replication and forwarding control based on node surroundings in cooperative delay-tolerant networks[J]. IEEE Transactions on Parallel&Distributed Systems, 2015, 26(10):2711-2719.
[9]WEI K, GUO S, ZENG D, et al. Exploiting small world properties for message forwarding in delay tolerant networks[J]. IEEE Transactions on Computers, 2015, 64(10):2809-2818.
[10]MERGENCI C, KORPEOGLU I. Routing in delay tolerant networks with periodic connections[J]. EURASIP Journal on Wireless Communications&Networking, 2015, 2015(1):1-19.
[11]WANG H Z, LV H W, WANG H Q, et al. DCAR:DTN congestion avoidance routing algorithm based on tokens in an urban environment[J]. Journal of Sensors, 2017, 2017:Article ID6523076.
[12]WANG H Z, FENG G S, WANG H Q, et al. RABP:Delay/disruption tolerant network routing and buffer management algorithm based on weight[J]. International Journal of Distributed Sensor Networks, 2018, 14(3):155014771875787.
[13]VAHDAT A. Epidemic routing for partially-connected Ad Hoc networks[D]. Durham, NC:Duke University, 2000:1-14.
[14]LINDGREN A, DORIA A, SCHELEN O. Probabilistic routing in intermittently connected networks[J]. Mobile Computing and Communications Review, 2003, 7(3):19-26.
[15]SPYROPOULOS T, PSOUNIS K, RAGHAVENDRA C S. Spray and wait:an efficient routing scheme for intermittently connected mobile networks[C]//Proceedings of the 2005 ACM International Conference on the Applications, Technologies, Architectures, and Protocols for Computer Communication. New York:ACM, 2005:252-259.
[16]EKMAN F, KARVO J. Working day movement model[C]//Proceedings of the 1st ACM Special Interest Group on Mobility of Systems,Users, Data, and Computing. New York:ACM, 2008:33-40.
[17]黄晓军. DTN拥塞控制机制及其应用研究[D].长沙:湖南大学,2013:33-37.(HUANG X J. Research on congestion control mechanism for DTN and its application[D]. Changsha:Hunan University, 2013:33-37.)