野战地域网拥塞控制方法及QoS路由蚁群算法
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摘要
未来战争是信息技术的战争，作为信息化战争的重要组成部分——野战地域通信网，成为各国军方研究的焦点。本文针对野战地域通信网的拥塞控制方案的安全性和QoS路由算法问题进行研究。
文章第二章，用对策论的相关理论讨论了常用拥塞控制策略的安全性。首先通过分析现有拥塞控制的对策论模型的不足之处，建立起存在恶意局中人的分步对策模型，该模型能够较好的刻画野战地域网络中的敌我对抗关系。之后给出了该对策模型的迭代数值解法和分析解法，并就FIFO，GPS和DWS三种调度策略给出对策模型Nash意义下的解。最后给出各种调度策略的安全性分析。
文章第三章针对野战地域网络特点，设计了双向搜索分布式蚁群算法(BDACRA)用以解决野战地域网的QoS路由问题，并给出了算法的收敛性证明。BDACRA通过“树形扩散”和“双向搜索”两种手段BDACRA的通信开销。最后通过分析和Matlab仿真，对比BDACRA和DACRA的时间复杂度、空间复杂度和通信开销。结果表明BDACRA较之DACRA具有更好的表现。
文章最后对全文作了总结，指出模型善未解决的问题及下一步的研究方向。
Future warfare will pay more attention to Information Technology. Regional Communication Network (RCN), an important part of the Information Warfare, is gradually becoming the focus of armies. This thesis mainly discusses two topics on RCN: The security of congestion control mechanism & QoS Routing Algorithm.
In Chapter 2, the security of congestion control mechanism is investigated through game theory. First, by analyzing the disadvantages existing in present game theory models used in congestion control, a step-to-step game theory model which contains malicious players is developed. The model can well describe the counter relationship between us and the enemy. Then, give the iterative numerical methodology and the analytical methodology to solve it, and get the solution under the Nash on FIFO, GPS and DWS scheduling techniques. At last, the security of all scheduling techniques is analysed.
In Chapter 3, by considering the characteristics of RCN, the paper develops a BDACRA (Bidirectional Distribution Ant Colony Routing Algorithm) to solve QoS routing problem in RCN, and also discuss the convergence of it. To reduce the communication costs of BDACRA, both "Tree-style Diffusing" and "Bidirectional Detecting" are adopted in the algorithm. At last, the paper compares time complexes, space complexes and communication costs between BDACRA and DACRA by analytical method and Matlab simulation. All results show that BDACRA has a better performance than DACRA.
The last chapter of the paper gives a conclusion of the article and presents the unsolved problems in the paper as well as the future investigations.
文章第二章，用对策论的相关理论讨论了常用拥塞控制策略的安全性。首先通过分析现有拥塞控制的对策论模型的不足之处，建立起存在恶意局中人的分步对策模型，该模型能够较好的刻画野战地域网络中的敌我对抗关系。之后给出了该对策模型的迭代数值解法和分析解法，并就FIFO，GPS和DWS三种调度策略给出对策模型Nash意义下的解。最后给出各种调度策略的安全性分析。
文章第三章针对野战地域网络特点，设计了双向搜索分布式蚁群算法(BDACRA)用以解决野战地域网的QoS路由问题，并给出了算法的收敛性证明。BDACRA通过“树形扩散”和“双向搜索”两种手段BDACRA的通信开销。最后通过分析和Matlab仿真，对比BDACRA和DACRA的时间复杂度、空间复杂度和通信开销。结果表明BDACRA较之DACRA具有更好的表现。
文章最后对全文作了总结，指出模型善未解决的问题及下一步的研究方向。
Future warfare will pay more attention to Information Technology. Regional Communication Network (RCN), an important part of the Information Warfare, is gradually becoming the focus of armies. This thesis mainly discusses two topics on RCN: The security of congestion control mechanism & QoS Routing Algorithm.
In Chapter 2, the security of congestion control mechanism is investigated through game theory. First, by analyzing the disadvantages existing in present game theory models used in congestion control, a step-to-step game theory model which contains malicious players is developed. The model can well describe the counter relationship between us and the enemy. Then, give the iterative numerical methodology and the analytical methodology to solve it, and get the solution under the Nash on FIFO, GPS and DWS scheduling techniques. At last, the security of all scheduling techniques is analysed.
In Chapter 3, by considering the characteristics of RCN, the paper develops a BDACRA (Bidirectional Distribution Ant Colony Routing Algorithm) to solve QoS routing problem in RCN, and also discuss the convergence of it. To reduce the communication costs of BDACRA, both "Tree-style Diffusing" and "Bidirectional Detecting" are adopted in the algorithm. At last, the paper compares time complexes, space complexes and communication costs between BDACRA and DACRA by analytical method and Matlab simulation. All results show that BDACRA has a better performance than DACRA.
The last chapter of the paper gives a conclusion of the article and presents the unsolved problems in the paper as well as the future investigations.
引文
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[11] 王重钢，隆克平．分组交换网络中队列调度算法的研究及其展望．电子学报，2001，29(4)：553-559．
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[44] Chen T W, Tsai J T, Gerla M. QoS Routing Performance in Multihop, Multimedia Wireless Network. IEEE International Conference on Universal Personal Communications '97 October 1997, Part 2: 451-557.
[45] Sinpa P, Sivakumar R, Bhanrghavan V. CEDAR: A Core Extraction Distributed Ad Hoc routing algorithm. IEEE Infocom'99, New York, March 1998.
[46] Lorenz H, Orda Ariel. Optimal partition of QoS requirements on unicast paths and multicast trees. IEEE INFOCOM'99, March 1999: 246-253.
[47] Fortz B, Thorup M. Internet traffic engineering by optimizing OSPF weights. IEEE INFOCOM'00, vol 2, 2000: 519-528.
[48] Juttner A, Szviatovski B, Mecs I et al. Lagrange Relaxation Based Method for the QoS Routing Problem. IEEE INFOCOM'01, vol 2, 2001: 859-868.
[49] Raz D, Shavitt Y, Danny Raz, Yuval Shavitt. Optimal Partition of QoS requirements with Discrete Cost Functions. IEEE INFOCOM'00, vol 2, 2000: 613-622.
[50] Korkmaz T, Krunz M. Multi-Constrained Optimal Path Selection. IEEE INFOCOM'01, vol 2, 2000: 834-843.
[51] Shaikh A, Rexford J, Shin K G. Evaluating the impact of stale link state on quality-of-service routing. IEEE/ACM Transactions on Networking, April 2001, 9(2): 162-176.
[52] Funda Ergun, Rakesh Sinha, Lisa Zhang. QoS Routing with Performance-Dependent Costs. IEEE INFOCOM'00 March, 2000.
[53] Mohamed G, Schneider M. Maximizable Routing Metrics. IEEE/ACM TRANSACTION ON NETWORKING, AUGUST 2003, 11(4): 663-675.
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[2] 王金龙，王呈贵，吴起晖，龚玉萍．Ad Hoc移动无线网络．北京：国防工业出版社，2004：309-311．
[3] 李耐和．美国陆军通信带宽需求及能力分析．电子产品世界，2004，9：132-135．
[4] 刘建国，柯钰，钟京立．军事通信网络基础教程．北京：北京航空航天大学出版社，2001：198-206．
[5] 林闯，单志广，任丰原．计算机网络的服务质量．北京：清华大学出版社，2004：73-100．
[6] Crawley E, Nair R, Rajagolan B, Sandick H. A framework for QoS-based routing in the internet. IETF RFC 2386, August 1998.
[7] Hutchision D, Coulson G, Campbell A et al. Quality of Service Management in Distributed Systems. Network and Distributed Systems Management, Sloman M, ed 1994: Chapter 11.
[8] Garey M S, Johnson D S. Computers and intractability: a guide to the theory of NP-completeness. Oxford: Freeman, W H, 1979.
[9] 任丰原，林闯，刘卫东．IP网络中的拥塞控制．计算机学报，2003，26(9)：1025-1034．
[10] Jacobson V. Congestion avoidance and control. ACM Computer Communication Review, 1998, 18(4): 314-329.
[11] 王重钢，隆克平．分组交换网络中队列调度算法的研究及其展望．电子学报，2001，29(4)：553-559．
[12] 王宏宇，顾冠群．集成服务网络中的分组调度算法研究综述．计算机学报，1999，22(10)：1090-1099．
[13] Chao H J, Guo Xiaolei. Quality of Service Control in High-Speed Networks. John Wiley & Sons, Inc 2002, EISBN: 0471003972.
[14] Clark D D, Shenker S, Zhang L. Supporting Real-time Applications in Integrated Service Packer Network: Architecture and Mechanism. Proc ACM SIGCOMM, Aug 1992: 14-26.
[15] Chiopalkatti R, Kurose J, Towsley D. Scheduling policies for real-time and non-real-time traffic in a statistical multiplexer. IEEE INFOCOM'89, Ottawa, Canada, April 1989: 774-783.
[16] Shimonishi H, Yoshida M. An improvement of weighted round robin cell scheduling in ATM networks. Proc of IEEE Globecom'97, Vol 2, 1997:1119-1183.
[17] Shreedhar M, Varghese G. Efficient fair queuing using deficit round-robin. IEEE Transaction on Network, 1996, 4(3): 375-385.
[18] Parekh A K, Gallager R G. A generalized processor sharing approach to flow control in integrated services network: the single node case. IEEE/ACM Transaction on Network, Jun, 1993, 1(3): 344-357.
[19] Parekh A K, Gallager R G. A generalized processor sharing approach to flow control in integrated services network: the multiple node case. IEEE/ACM Transaction on Network, Apr, 1994, 2(2): 137-150.
[20] Parekh A K, Gallager R G. A generalized processor sharing approach to flow control in integrated services network: The single node case. IEEE INFOCOM'92, 1992.
[21] Bennett J C R, Zhang Hui. WF2Q: Worst-case fair weighted fair queuing. IEEE INFOCOM'96, Vol 1, San Francisco, CA, March, 1996: 120-128.
[22] Bennett J C R, Zhang Hui. Hierarchical packet fair queuing algorithm. IEEE/ACM Transaction on Networking, 1997, 5(5): 675-689.
[23] Zhang L. Virtual Clock: A new traffic control algorithm for packet switching. ACM Transaction Computer System, 1991: 101-124.
[24] Stiliadis D, Varma A. Efficient fair queuing algorithm for packet-switch networks. IEEE/ACM Transaction on Networking, 1998, 6(2): 175-185.
[25] Golestani S J. A self-clocked fair queuing scheme for broadband application. In: IEEE INFOCOM'94, Toronto, June 1994: 634-646.
[26] Goyal P, Vin H M, and Cheng H. Star-Time fair queuing: A scheduling algorithm for integrated services packet switched networks. IEEE Transaction on Networking, May 1997: 690-704.
[27] Stiliadis D, Varma A. Efficient fair queuing algorithm for packet-switched network. IEEE/ACM Transaction on Networking, 1998, 6(2): 175-185.
[28] Garg R., Kamra A and Khurana V. A Game-Theoretic Approach towards Congestion Control in Communication Networks. ACM SIGCOMM Computer Communications Review, July 2002, 32(3): 47-61.
[29] Aimal Tariq Rextin, Zahid Irfan. Games Networks Play, Game Theory and Congestion Control in Networks. CS-678 Topics in Internet Research: 1-10.
[30] Aditya Akella, Richard Karp, Scott Shenker. Selfish Behavior and Stability of the Internet: A Game-Theoretic Analysis of TCP. SIGCOMM'02, August 19-23, 2002, Pittsburgh, Pennsylvania, USA.
[31] Key P, McAuley D. Differential QoS and pricing in networks: where flow-control meets game theory. In IEEE Proceedings Software, 1999.
[32] Menashe D S, Figueredo D R, Souzae Silva E. An evolutionary game-theoretic approach to congestion control. Performance Evalution 62, 2005: 295-312.
[33] 魏蛟龙，张弛．Internet拥塞控制和资源分配中的对策论分析框架．电子学报，2003，31(10)：1452-1455．
[34] Debojyoti Dutta, Ashish Goel John Heidemann. Oblivious AQM and Nash Equilibria. IEEE INFOCOM 2003, 0-780307753-2/03.
[35] 刘德铭，黄振高．对策论及其应用．北京：国防科技大学出版社，1995：67．
[36] Karp R, Koutsoupias E, Papadimitriou C, Shenker S. Combinatorial optimization in congestion control. Proceedings of the 41'Th Annual Symposium on Foundations of Computer Science, Redondo Beach, CA, 12-14 Nov 2000: 66-74.
[37] 侯维娜，赵为粮．Ad hoe网络中的路由和QoS路由．计算机与信息技术，2004(3)．
[38] Perkins C E, Bhagwat P. Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers. Computer Communication Review, Oct 1994: 234-244.
[39] David B J, David A M, Hu Y C. The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (DSR). INTERNET-DRAFT, Internet Engineering Task Force, July 2004.
[40] Perkins C, Belding R E. Ad hoc On-Demand Distance Vector (AODV) Routing. RFC 3561, Internet Engineering Task Force, July 2003.
[41] Clausen T, Jacquet P. Optimized Link State Routing Protocol (OLSR). FC3626, Internet Engineering Task Force, October 2003.
[42] Toh C K. Associativity-Based Routing for Ad-Hoc Mobile Networks. Wireless Personal Communications Journal, March 1997, 4(2): 103-139.
[43] 郑少仁，王海涛，赵志峰．Ad Hoc网络技术．北京：人民邮电出版社，2005：69-70．
[44] Chen T W, Tsai J T, Gerla M. QoS Routing Performance in Multihop, Multimedia Wireless Network. IEEE International Conference on Universal Personal Communications '97 October 1997, Part 2: 451-557.
[45] Sinpa P, Sivakumar R, Bhanrghavan V. CEDAR: A Core Extraction Distributed Ad Hoc routing algorithm. IEEE Infocom'99, New York, March 1998.
[46] Lorenz H, Orda Ariel. Optimal partition of QoS requirements on unicast paths and multicast trees. IEEE INFOCOM'99, March 1999: 246-253.
[47] Fortz B, Thorup M. Internet traffic engineering by optimizing OSPF weights. IEEE INFOCOM'00, vol 2, 2000: 519-528.
[48] Juttner A, Szviatovski B, Mecs I et al. Lagrange Relaxation Based Method for the QoS Routing Problem. IEEE INFOCOM'01, vol 2, 2001: 859-868.
[49] Raz D, Shavitt Y, Danny Raz, Yuval Shavitt. Optimal Partition of QoS requirements with Discrete Cost Functions. IEEE INFOCOM'00, vol 2, 2000: 613-622.
[50] Korkmaz T, Krunz M. Multi-Constrained Optimal Path Selection. IEEE INFOCOM'01, vol 2, 2000: 834-843.
[51] Shaikh A, Rexford J, Shin K G. Evaluating the impact of stale link state on quality-of-service routing. IEEE/ACM Transactions on Networking, April 2001, 9(2): 162-176.
[52] Funda Ergun, Rakesh Sinha, Lisa Zhang. QoS Routing with Performance-Dependent Costs. IEEE INFOCOM'00 March, 2000.
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