下一代互联网QoS关键技术研究
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摘要
下一代互联网研究的核心是构建满足未来网络与业务需求的新型互联网体系结构,QoS保障是其中最重要的一项核心服务。未来互联网要求一系列增强的特性和功能,包括更高的转发速度、更大的地址空间,以及更强的自管理与自适应能力。未来网络中日趋多样化的业务需求与复杂多变的网络环境,使构建和设计高效QoS管理架构与高性能QoS保障机制成为下一代互联网研究中一项极具挑战性的任务。
论文研究下一代互联网体系结构中QoS保障的若干关键技术。针对未来网络QoS保障体系对高速分组处理的要求,论文研究高性能的QoS保障机制,提出了新型的高性能分组分类器算法。为解决复杂动态的未来网络环境中的QoS保障问题,论文将自治化属性引入下一代互联网的QoS保障体系,研究和提出支持上下文感知与自管理能力的自治QoS管理框架和保障机制,其中重点研究了上下文感知的分组标记器和队列管理机制。论文的主要研究内容包括：
(一)、提出了一种高速分组分类算法：增强递归流分类(ERFC),解决原有递归流分类(RFC)算法预处理复杂度高、空间需求大的问题。ERFC采用基于散列的聚合比特向量算法,大幅降低了预处理的复杂度；采用支持高速缓存的压缩搜索结构降低了空间复杂度,并进一步提高了分类速度。性能评估结果表明,算法在预处理、分类速度和空间复杂度等方面的性能均比现有算法有大幅提高。
(二)、提出了一种支持IPv6的、基于高效多比特选择(EMBS)的决策树分组分类算法。EMBS(?)将决策树的建立变换为一系列前缀比特的选择过程,采用一种高效的多比特选择算法和性能评估函数(PEF),使决策树具有更高时间和空间性能。算法支持范围匹配,适用于IPv4和IPv6环境。性能评估结果表明,在IPv4/IPv6的多种应用场景下,该算法的整体性能均明显高于现有的其他分组分类算法。
(三)、研究了自治DiffServ QoS管理框架的若干关键技术,包括管理框架、上下文感知与分发、QoS机制等；提出了一种上下文感知的分组标记器(CAPM)。CAPM具有上下文感知能力,通过感知网络／业务的状态以及业务流的语义,利用自治反馈控制,自适应性地对其标记行为进行动态调整,提高业务流的传输质量。仿真结果表明,CAPM可大幅提高多媒体视频业务的传输质量,改善用户的服务体验。
(四)、提出了自治DiffServ管理框架中一种上下文感知的队列管理机制(CAQM)。CAQM支持与CAPM标记器之间的协作与上下文交互,提供基于上下文感知和语义识别的分组差异化处理。CAQM利用多等级子队列结构来管理汇聚流中的多个传输优先级,并利用传输优先级中蕴含的业务语义进行拥塞控制,提高了业务流中关键信息的传输质量。仿真结果表明,在自治网络环境下,通过与CAPM标记器的协作,CAQM进一步提高了多媒体视频业务的传输质量和用户的服务体验。
The most important research focus in the field of Next Generation Internet (NGI) is to research and construct new network architectures to meet the requirements of users and services in the future Internet, in which QoS (Quality of Service) guarantee is also one of the most fundamental network services. A series of new characteristics and enhanced functionalities are required in the future Internet, which include higher forwarding speed, larger address space, and abilities of self-management and self-adaptation. Increasingly diversified service requirements and more complex dynamic network environments of the future Internet make it a challenging task to design efficient QoS management architectures and high performance QoS guarantee mechanisms in the next generation Internet.
In this dissertation, several key technologies of QoS guarantee in the next generation Internet are studied in detail. For requirements of high speed packet processing in the QoS management of future Internet, high performance QoS guarantee mechanisms are studied in the dissertation, and novel high speed packet classification algorithms are proposed. To address QoS issues in the increasingly complex and dynamic environment of the future network, autonomic attributes are introduced into the architecture design of the next generation Internet and its QoS management framework. Novel solutions of QoS management and context-aware autonomic QoS mechanisms (packet marking and queue management) are proposed. The main contributions of the dissertation include:
(1) A high speed packet classification algorithm, ERFC (Enhanced Recursive Flow Classification), is proposed to solve the problem of high space and preprocessing complexity in the original RFC (Recursive Flow Classification) algorithm. In ERFC, a hash-based aggregated bit vector scheme is exploited to speed up its preprocessing procedure, and a compressed and cacheable data structure is introduced to decrease total memory requirement and improve searching performance. Evaluation results show that ERFC provides a great performance improvement over RFC in space requirement, preprocessing time and search speed.
(2) A novel decision tree packet classification algorithm based on Efficient Multiple Bit Selection (EMBS) is proposed. In the proposed algorithm, the process of building the decision tree is transformed to a sequence of prefix bit selecting procedures. A Performance Estimate Function (PEF) and an efficient bit selecting algorithm are exploited to determine which selection will lead to an efficient decision tree with high performance. EMBS algorithm is capable of handling range match fields, is suitable for IPv6packet classification as well as IPv4. Evaluation results show that EMBS provides a great improvement over recent decision tree based algorithms in both space requirement and searching performance.
(3) Some key issues in the autonomic DiffServ QoS management architecture are studied, which include QoS management framework, context awareness and dissemination, and design of autonomic QoS mechanisms. In this dissertation, a context-aware packet marking (CAPM) algorithm is proposed. CAPM collects various types of contexts, such as service status, network conditions, and semantic priorities of packets in service flows. Based on context analyzing and autonomic feedback controlling, it is capable of adaptively adjusting its behavior to provide better QoS guarantee. Simulation results show that, CAPM provides better transmission quality for multimedia streaming video services than traditional packet marker, and significantly improves user's quality of experience.
(4) In the autonomic DiffServ QoS management framework, a context-aware queue management (CAQM) mechanism is also proposed. CAQM is capable of collaborating and exchanging contexts with CAPM, and provides differentiated packet processing based on semantic contexts. In CAQM, a multi-level sub-queue structure is used to manage different packet priorities in aggregated flows. In order to improve the transmission quality of critical data packets of service flows, the congestion control of CAQM is performed based on packet priorities which imply service semantics. Simulation results show that, collaborating with CAPM in autonomic DiffServ network environment, CAQM will further improve the transmission quality and user experience of streaming video service.
论文研究下一代互联网体系结构中QoS保障的若干关键技术。针对未来网络QoS保障体系对高速分组处理的要求,论文研究高性能的QoS保障机制,提出了新型的高性能分组分类器算法。为解决复杂动态的未来网络环境中的QoS保障问题,论文将自治化属性引入下一代互联网的QoS保障体系,研究和提出支持上下文感知与自管理能力的自治QoS管理框架和保障机制,其中重点研究了上下文感知的分组标记器和队列管理机制。论文的主要研究内容包括：
(一)、提出了一种高速分组分类算法：增强递归流分类(ERFC),解决原有递归流分类(RFC)算法预处理复杂度高、空间需求大的问题。ERFC采用基于散列的聚合比特向量算法,大幅降低了预处理的复杂度；采用支持高速缓存的压缩搜索结构降低了空间复杂度,并进一步提高了分类速度。性能评估结果表明,算法在预处理、分类速度和空间复杂度等方面的性能均比现有算法有大幅提高。
(二)、提出了一种支持IPv6的、基于高效多比特选择(EMBS)的决策树分组分类算法。EMBS(?)将决策树的建立变换为一系列前缀比特的选择过程,采用一种高效的多比特选择算法和性能评估函数(PEF),使决策树具有更高时间和空间性能。算法支持范围匹配,适用于IPv4和IPv6环境。性能评估结果表明,在IPv4/IPv6的多种应用场景下,该算法的整体性能均明显高于现有的其他分组分类算法。
(三)、研究了自治DiffServ QoS管理框架的若干关键技术,包括管理框架、上下文感知与分发、QoS机制等；提出了一种上下文感知的分组标记器(CAPM)。CAPM具有上下文感知能力,通过感知网络／业务的状态以及业务流的语义,利用自治反馈控制,自适应性地对其标记行为进行动态调整,提高业务流的传输质量。仿真结果表明,CAPM可大幅提高多媒体视频业务的传输质量,改善用户的服务体验。
(四)、提出了自治DiffServ管理框架中一种上下文感知的队列管理机制(CAQM)。CAQM支持与CAPM标记器之间的协作与上下文交互,提供基于上下文感知和语义识别的分组差异化处理。CAQM利用多等级子队列结构来管理汇聚流中的多个传输优先级,并利用传输优先级中蕴含的业务语义进行拥塞控制,提高了业务流中关键信息的传输质量。仿真结果表明,在自治网络环境下,通过与CAPM标记器的协作,CAQM进一步提高了多媒体视频业务的传输质量和用户的服务体验。
The most important research focus in the field of Next Generation Internet (NGI) is to research and construct new network architectures to meet the requirements of users and services in the future Internet, in which QoS (Quality of Service) guarantee is also one of the most fundamental network services. A series of new characteristics and enhanced functionalities are required in the future Internet, which include higher forwarding speed, larger address space, and abilities of self-management and self-adaptation. Increasingly diversified service requirements and more complex dynamic network environments of the future Internet make it a challenging task to design efficient QoS management architectures and high performance QoS guarantee mechanisms in the next generation Internet.
In this dissertation, several key technologies of QoS guarantee in the next generation Internet are studied in detail. For requirements of high speed packet processing in the QoS management of future Internet, high performance QoS guarantee mechanisms are studied in the dissertation, and novel high speed packet classification algorithms are proposed. To address QoS issues in the increasingly complex and dynamic environment of the future network, autonomic attributes are introduced into the architecture design of the next generation Internet and its QoS management framework. Novel solutions of QoS management and context-aware autonomic QoS mechanisms (packet marking and queue management) are proposed. The main contributions of the dissertation include:
(1) A high speed packet classification algorithm, ERFC (Enhanced Recursive Flow Classification), is proposed to solve the problem of high space and preprocessing complexity in the original RFC (Recursive Flow Classification) algorithm. In ERFC, a hash-based aggregated bit vector scheme is exploited to speed up its preprocessing procedure, and a compressed and cacheable data structure is introduced to decrease total memory requirement and improve searching performance. Evaluation results show that ERFC provides a great performance improvement over RFC in space requirement, preprocessing time and search speed.
(2) A novel decision tree packet classification algorithm based on Efficient Multiple Bit Selection (EMBS) is proposed. In the proposed algorithm, the process of building the decision tree is transformed to a sequence of prefix bit selecting procedures. A Performance Estimate Function (PEF) and an efficient bit selecting algorithm are exploited to determine which selection will lead to an efficient decision tree with high performance. EMBS algorithm is capable of handling range match fields, is suitable for IPv6packet classification as well as IPv4. Evaluation results show that EMBS provides a great improvement over recent decision tree based algorithms in both space requirement and searching performance.
(3) Some key issues in the autonomic DiffServ QoS management architecture are studied, which include QoS management framework, context awareness and dissemination, and design of autonomic QoS mechanisms. In this dissertation, a context-aware packet marking (CAPM) algorithm is proposed. CAPM collects various types of contexts, such as service status, network conditions, and semantic priorities of packets in service flows. Based on context analyzing and autonomic feedback controlling, it is capable of adaptively adjusting its behavior to provide better QoS guarantee. Simulation results show that, CAPM provides better transmission quality for multimedia streaming video services than traditional packet marker, and significantly improves user's quality of experience.
(4) In the autonomic DiffServ QoS management framework, a context-aware queue management (CAQM) mechanism is also proposed. CAQM is capable of collaborating and exchanging contexts with CAPM, and provides differentiated packet processing based on semantic contexts. In CAQM, a multi-level sub-queue structure is used to manage different packet priorities in aggregated flows. In order to improve the transmission quality of critical data packets of service flows, the congestion control of CAQM is performed based on packet priorities which imply service semantics. Simulation results show that, collaborating with CAPM in autonomic DiffServ network environment, CAQM will further improve the transmission quality and user experience of streaming video service.
引文
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