基于人工免疫的聚合重构资源自治分配

doi:10.13190/jbupt.201002.82.hu

北京邮电大学学报 ›› 2010, Vol. 33 ›› Issue (2): 82-87.doi: 10.13190/jbupt.201002.82.hu

基于人工免疫的聚合重构资源自治分配

胡铮, 张国翊, 田辉

（泛网无线通信教育部重点实验室(北京邮电大学)，北京 100876）

收稿日期:2009-07-03 修回日期:2009-10-10 出版日期:2010-04-28 发布日期:2010-04-28
通讯作者: 张国翊
作者简介:胡铮(1980—)，男，博士，讲师；张国翊(1982—)，男，博士生， Email: zgysam@gmail.com.
基金资助:
国家重大专项项目(2009ZX03004001)；国家重点基础研究计划项目(2009CB320406)；国家高技术发展研究计划项目(2009AA01Z262)；国家自然科学基金项目(60832009)

Artificial Immune System Based Autonomic Resource Allocation for Aggregation Reconfiguration

HU Zheng, ZHANG Guo-yi, TIAN Hui

(Key Laboratory of Universal Wireless Communications (Beijing University of Posts and Telecommunications), 
Ministry of Education, Beijing 100876, China)

Received:2009-07-03 Revised:2009-10-10 Online:2010-04-28 Published:2010-04-28

摘要/Abstract

摘要：

针对异构网络融合中的终端聚合重构模式，讨论了在付费激励机制下如何通过聚合资源提供者的动态定价来激励终端间的高效合作，引导系统资源分配的全局自治优化. 提出信息不完全情况下以人工免疫系统自适应控制模型为基础的自主定价方法（AISMAP）. 仿真结果表明，该方法能提高系统整体的资源收益，并能引导带宽资源分配自治实现全局均衡.

关键词: 聚合重构, 市场激励, 定价, 资源分配, 免疫系统

Abstract:

Aggregation reconfiguration assisted by the cooperation of terminals is a new paradigm for heterogeneous networks convergence. The marketbased incentive pay mechanism is investigated, and dynamic pricing is used to promote global optimization on resource allocation autonomously. With the consideration that the pricing decision will confront incomplete information, an adaptivecontrolbased pricing solution based on artificial immune system is proposed. Experiment shows that the artificial immune system model based automatic pricing (AISMAP) algorithm can improve resource utilization of whole system and autonomously guide the traffic resources allocation toward global balance.

Key words: aggregation reconfiguration, marketbased incentive, pricing, resource allocation, immune system

中图分类号:

TN393

胡铮张国翊田辉. 基于人工免疫的聚合重构资源自治分配[J]. 北京邮电大学学报, 2010, 33(2): 82-87.

HU Zheng, ZHANG Guo-yi, TIAN Hui. Artificial Immune System Based Autonomic Resource Allocation for Aggregation Reconfiguration[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2010, 33(2): 82-87.

参考文献

[1] Zhang Ping, Ji Yang. The vision of mobile ubiquitous service environment and several challenges for the architecture design[J]. Journal of Beijing University of Posts and Telecommunications, 2005, 28(37): 1-4.
[2] Chen Xiaomei, Lu Xicheng, Wang Huaimin. Research on network resaource allocation based on microeconomic theory: a survey[J]. Journal of Computer Research and Development, 2001, 38(11): 1344-1353.
[3] Kelly F P. Models for a self-managed Internet[J]. Philosophical Transactions of the Royal Society of London, 2000, A358: 2334-2348.
[4] Paschalidis I C, Liu Yong. Pricing in multiservice loss networks: static pricing asymptotic optimality, and demand substitution effects[J]. IEEE/ACM Transactions on Networking, 2002(10): 425-438.
[5] Zhang Yongjing, Zhang Ping. Markov game for autonomic joint radio resource management in a multi-operator scenario[J]. The Journal of China Universities of Posts and Telecommunications, 2007, 14(3): 48-55.
[6] Jerne N K. Towards a network theory of the immune system[J]. Annals Dimmunologie, 1974, 125(1-2): 373-389.
[7] Wang Weihong, Li Baochun. Market-based self-optimization for autonomic service overlay networks[J]. IEEE Journal on Selected Areas in Communications, 2005, 23(12): 2320-2332.
[8] 莫宏伟. 人工免疫系统原理与应用[M]. 哈尔滨工业大学出版社, 2003. (上接第77页)
[4] Xu Wenbo, Lin Jiaru, Niu Kai, et al. Perfor- mance analysis of ARQ schemes with code combining over Nakagami-m fading channel[J]. Journal of China University of Posts and Tele-communications, 2009, 16(5): 14-19.
[5] Filho J C S S, Yacoub M D. Nakagami-m appro-ximation to the sum of M non-identical inde-pendent Nakagami-m variates[J]. Electron Lett, 2004, 40(15): 951-952.
[6] Chen Qingchun, Fan Pingzhi. Performance analysis of hybrid ARQ with code combining over interleaved Rayleigh fading channel[J]. IEEE Trans Veh Technol, 2005, 54(3): 1207-1214.
[7] Noh K L, Serpedin E, Suter B. Optimum coope-ration of the cooperative coding scheme for frequency division half-duplex relay channels[J]. IEEE Trans Wireless Commun, 2007, 6(5): 1654-1658.
[8] Gradshteyn I S, Ryzhik I M. Table of integrals, series and products. 6th ed. New York: Academicy, 2000.
[9] Wang Zhengdao, Giannakis G B. A simple and general parameterization quantifying performance in fading channels[J]. IEEE Trans Commun, 2003, 51(8): 1389-1398.

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基于人工免疫的聚合重构资源自治分配

Artificial Immune System Based Autonomic Resource Allocation for Aggregation Reconfiguration

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