EIM: An Enforceable Incentive Mechanism for Dynamic Non-cooperative Multi-radio Channel Allocation in Wireless Mobile Networks

被引:0
|
作者
Zheng, Hongjiang [1 ]
Chen, Wei [2 ]
Zhu, Rongbo [3 ]
Feng, Wei [4 ]
机构
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Peoples R China
[2] Wuhan Univ Technol, Sch Automat, Wuhan 430070, Peoples R China
[3] South Cent Univ Nationalities, Coll Comp Sci, Wuhan 430074, Peoples R China
[4] China Transport Telecommun & Informat Ctr, MOT Transport Satellite Nav Industrializat Ctr, Beijing 100010, Peoples R China
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
Game theory; Multi-radio channel allocation; Enforceable incentive mechanism; Nash equilibriums (NEs); Mobile resource management;
D O I
10.1007/s11277-013-1313-7
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Multi-radio channel allocation (MRCA) is a key issue to improve the system performance supporting all kinds of mobile applications in wireless networks. However, existed work on non-cooperative MRCA just considers the cases under the extreme saturation load condition and static game, which means that it is assumed that all the nodes always have packets to send and mobile terminals just change the channel once. Such assumption is obviously impractical for actual wireless network and isn't suitable for the mobility of applications without intelligent spectrum management. Meanwhile, the existed schemes are unable to support mobile applications with time-varying channel. In this paper, an enforceable incentive mechanism called EIM is proposed for dynamic non-cooperative multi-radio channel allocation to support mobile applications. In order to optimize the overall performance of mobility management, in the proposed EIM, the strong assumption of saturation network traffic is relaxed, which makes the mobile terminals are able to have time-varying bandwidth requirements. Then, the MRCA problem is modeled as an infinite repeated game. Detailed theoretical analysis proves that there exist multiple pure Nash Equilibriums (NEs) for the game, and, under certain condition, there also exist NEs which are not Pareto-Optimal. Hence, based on the punishment strategy, the proposed EIM can achieve social welfare. Detailed numerical and simulation results show that the proposed EIM can improve the system throughput about 15 % compared with the existed works, which can provide an efficient method to manage channel resource and get better ubiquitous online access to preferred mobile services.
引用
收藏
页码:829 / 851
页数:23
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