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Multiplicative multi-attribute auction based optimal network selection for heterogeneous wireless networks 被引量：4

Multiplicative multi-attribute auction based optimal network selection for heterogeneous wireless networks
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摘要 One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly. However, most of previous work only takes account of either maximizing single user＇s utility or the whole network＇s payoff, rarely considers the negotiation between them. In this paper, we propose a novel network selection approach using improved multiplicative multi-attribute auction （MMA）. At first, an improved MMA method is put forward to define the user＇s utility. Additionally, user cost is defined by considering allocated bandwidth, network load intensity and cost factor parameter. And last the best suitable network is selected according to the user＇s performance-cost-ration. Simulation results confirm that the proposed scheme outperforms the existing scheme in terms of network selection＇s fairness, user＇s performance-cost-ration, load balancing and the number of accommodated users. One of the remarkable features of the next generation network is the integration of heterogeneous wireless networks, which enables mobile users with multi-mode terminals access to the best available network seamlessly. However, most of previous work only takes account of either maximizing single user＇s utility or the whole network＇s payoff, rarely considers the negotiation between them. In this paper, we propose a novel network selection approach using improved multiplicative multi-attribute auction （MMA）. At first, an improved MMA method is put forward to define the user＇s utility. Additionally, user cost is defined by considering allocated bandwidth, network load intensity and cost factor parameter. And last the best suitable network is selected according to the user＇s performance-cost-ration. Simulation results confirm that the proposed scheme outperforms the existing scheme in terms of network selection＇s fairness, user＇s performance-cost-ration, load balancing and the number of accommodated users.
作者 ZHAI Lan-jie JI Hong LI Xi ZHANG Xiao-liang
机构地区 School of Information and Communication Engineering
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2012年第4期1-5,共5页 中国邮电高校学报（英文版）
基金 supported by the National Natural Science Funds of China for Young Scholar (61001115) the Fundamental Research Funds for the Central Universities of China (2012RC0126,2011RC0110)
关键词 multiplicative multi-attribute auction network selection user＇s performance-cost-ration network load intensity multiplicative multi-attribute auction, network selection, user＇s performance-cost-ration, network load intensity
分类号 TP308 [自动化与计算机技术—计算机系统结构] TN929.53 [电子电信—通信与信息系统]
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参考文献9

  • 1Nguyen-Vuong Q T, Ghamri-Doudane Y, Agoulmine N. On utility models for access network selection in wireless heterogeneous networks. Proceeding of the 10th IEEE/IFIP Network Operations and Management Symposium (NOMS'08), Apt 7-11, 2008, Salvador de Bahia, Brazil. Piscataway, NJ, USA: IEEE, 2008:144-151.
  • 2Pei X B, Jiang T, Qu D M, et al. Radio-resource management and access-control mechanism based on a novel economic model in heterogeneous wireless networks. IEEE Transactions on Vehicular Technology, 2010, 59(6): 3047-3056.
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同被引文献23

  • 1DIMITRIS D E, PANAGOPOULOS A D, MARKAKI O I. A unified network selection framework using principal component analysis and multi attribute decision making [ J ]. Wireless Personal Communi- cations ,2014,74( 1 ) : 147-165.
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  • 3LIU Xing-wei, FAN Xu-ming, CHEN Xu, et al. A bidding model and cooperative game-based vertical handoff decision algorithm [ J ]. Journal of Network and Computer Applications, 2011,34 (4) : 1263-1271.
  • 4CUI Yang, Xu Yu-bing, XU Rong-qing, et al. A heterogeneous wire- less network selection algorithm based on non-cooperative game theory [ C ]//Proc of the 6th International ICST Conference on Communica- tions and Networking. 2011:720-724.
  • 5PERVAIZ H, NI Qiang. User preferences-adaptive dynamic network selection approach in cooperating wireless networks:a game theoretic perspective[ C ]//Proc of the 11th IEEE International Conference on Trust, SecmJty and Privacy in Computing and Conununications. 2012: 1609-1616.
  • 6BARI F, LEUNG V C M. Use of non-monotonic utility in multi-at- tribute network selection[ J]. Wireless Telecommunications Sym- posium, 2009,44 : 21 - 39.
  • 7LIU S F, FORREST J. Advances in grey systems theory and its appli- cations[ C]//Proc of IEEE International Conference on Grey Systems and Intelligent Services. 2007:1-6.
  • 8MITCHELL T M. Machine learning [ M ]. New York : McGraw Hill, 1997.
  • 9MAILLE P, TUFFIN B. Price war in heterogeneous wireless networks [ J]. Computer Networks ,2010,54( 13 ) :2281-2292.
  • 10YAN Jun-hua, ZHANG Huan-chun, JING Ya-zhi. Load balancing of the distributed system based on multi-agent [ J ]. Journal of South China University of Technology: Natural Science ,2004,32 ( 12 ) : 74 - 79.

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The Journal of China Universities of Posts and Telecommunications
2012年 第4期

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