基于多方议价博弈的机会网络高吞吐量低开销概率路由算法

doi:10.11959/j.issn.1000-436x.2015129

摘要/Abstract

摘要：

针对含自私节点的机会网络中现有基于议价博弈的概率路由算法存在的消息单向传递影响转发概率提高、依赖虚拟货币进行交易削弱节点购买力以高及消息交易过程有冗余交互的问题，提出一种基于多方议价博弈的吞吐量低开销概率路由算法——HLPR-MG。HLPR-MG算法通过将节点两两博弈扩展为多方博弈以加快消息转发概率的提升，引入“以物易物”方式增强节点购买力，并且改进现有交互机制以减少博弈次数，从而达到提高网络吞吐量的和减小控制开销的效果。理论分析验证了HLPR-MG算法设计的有效性。仿真结果表明，与基于议价博弈的现有典型路由算法GSCP和BG相比，HLPR-MG算法的吞吐量和消息传送成功率至少提高了3.63%，而控制开销和平均端到端消息时延则分别降低超17.76%和4.03%。

关键词: 机会网络, 概率路由, 博弈, 吞吐量, 开销

Abstract:

To address the problems existing in the present probabilistic routing based on bargaining games,including unidirectional transmission of messages degrades the success ratio,depending on the virtual money decreases the purchasing power of nodes,and redundancy exists in the interaction process of messages,an routing algorithm based on multi-player bargaining game for opportunistic networks,HLPR-MG,was proposed.Through extending the two-player game to a multi-player bargaining game,introducing the barter trade to enhance purchasing power of nodes,and improving the existing interaction mechanism to reduce the times of game,proposed algorithm achieves the effect of increasing network throughput and decreasing control overhead.Theoretical analysis verifies the effectiveness of HLPR-MG,and simulation results show that HLPR-MG improves the network throughput and success ratio at least 3.63%,and reduces the control overhead and average end-to-end delay by more than 17.76% and 4.03%,respectively,as compared to the classical GSCP and BG algorithms.

Key words: opportunistic networks, probabilistic routing, game, throughput, overhead

任智,索建伟,刘文朋,雷宏江,陈前斌. 基于多方议价博弈的机会网络高吞吐量低开销概率路由算法[J]. 通信学报, 2015, 36(6): 41-48.

Zhi REN,Jian-wei SUO,Wen-peng LIU,Hong-jiang LEI,Qian-bin CHEN. High-throughput and low-overhead probabilistic routing based on multi-player bargaining game for opportunistic networks[J]. Journal on Communications, 2015, 36(6): 41-48.

图/表 9

图1

图2

图3

图4

表1

图5

图6

图7

图8

参考文献 15

[1]	熊永平, 孙利民, 牛建伟 ,等. 机会网络[J]. 软件学报, 2009,20(1): 124-137. XIONG Y P , SUN L M , NIU J W ,et al. Opportunistic networks[J]. Journal of Software, 2009,20(1): 124-137.
[2]	任智, 黄勇, 陈前斌 . 机会网络路由协议[J]. 计算机应用, 2010,30(3): 723-728. REN Z , HUANG Y , CHEN Q B . Routing protocols for opportunistic networks[J]. Journal of Computer Applications, 2010,30(3): 723-728.
[3]	叶晖, 陈志刚, 赵明 . ON-CRP:机会网络缓存替换策略研究[J]. 通信学报, 2010,31(5): 98-107. YE H , CHEN Z G , ZHAO M . ON-CRP:cache replacement policy for opportunistic networks[J]. Journal on Communications, 2010,31(5): 98-107.
[4]	刘乔寿, 周建二, 张普宁 . 机会网络中基于消息副本数量的自适应缓存管理策略[J]. 重庆邮电大学学报(自然科学版), 2012,23(4): 394-399. LIU Q S , ZHOU J E , ZHANG P N . Adaptive cache management method for opportunistic network based on number of message copies[J]. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2012,23(4): 394-399.
[5]	RESTA G , SANTI G . A framework for routing performance analysis in delay tolerant networks with application to non-cooperative networks[J]. IEEE Transactions on Parallel and Distributed Systems, 2011,23(1): 2-10.
[6]	FRIEDMAN D . On economic applications of evolutionary game theory[J]. Journal of Evolutionary Economics, 1998,8(1): 15-43.
[7]	唐作用, 袁艺嘉, 董永强 ,等. 基于信誉值维护的机会网络自私节点检测机制[J]. 通信学报, 2013,33(z2): 217-221. TANG Z Y , YUAN Y J , DONG Y Q ,et al. Detection of selfish nodes based on credit mechanism in opportunistic networks[J]. Journal on Communications, 2012,33(z2): 217-221.
[8]	BIGWOOD G , TRISTAN H . IRONMAN:Using social networks to add incentives and reputation to opportunistic networks[A]. 2011 IEEE International Conference on Privacy,Security,Risk,and Trust,and IEEE International Conference on Social Computing,IEEE[C]. 2011. 65-72.
[9]	BIGWOOD G , TRISTAN H . Incentive-aware opportunistic networkrouting[J]. Routing in Opportunistic Networks, 2013,14: 383-401.
[10]	汪洋, 林闯, 李泉林 ,等. 基于非合作博弈的无线网络路由机制研究[J]. 计算机学报, 2009,32(1): 54-68. WANG Y , LIN C , LI Q L ,et al. Non-cooperative game based research on routing schemes for wireless networks[J]. Journal of Computers, 2009,32(1): 54-68.
[11]	BUTTYAN L , DORA L , FELEGYHAZI M ,et al. Barter trade improves message delivery in opportunistic networks[J]. Ad Hoc Networks, 2010,8(1): 1-14.
[12]	WU F , CHEN T , ZHONG S ,et al. A game-theoretic approach to stimulate cooperation for probabilistic routing in opportunistic networks[J]. IEEE Transactions on Wireless Communications, 2013,12(4): 1573-1583.
[13]	任智, 黄勇, 曹建玲 ,等. 基于邻居信息交换的机会网络低时延路由算法[J]. 华中科技大学学报(自然科学版), 2011,39(2): 94-97. REN Z , HUANG Y , CAO J L ,et al. Low-delay routing algorithm for opportunistic networks by exchanging the neighborhood information[J]. Journal of Huangzhong University of Science and Technology (Natural Science Edition), 2011,39(2): 94-97.
[14]	LINDGREN A , DORIA A , SCHELEN O . Probabilistic routing in intermittently connected networks[J]. ACM Sigmobile Mobile Computing and Communications Review, 2003,7(3): 19-20.
[15]	ZUO F , WEI Z . An evolutionary game-based mechanism for routing P2P network flow among selfish peers[J]. Journal of Networks, 2014,9(1): 10-17.

参数	数值
仿真场景	1 500 m×300 m
节点运动速度/(m·s^?1)	1～19
传输速率/(Mbit·s^?1)	54
节点个数	50
自私节点所占比例/%	{0,25,50,75,100}
随机种子值	{64,128,256,512,1 024}
仿真时间/s	6 000
仿真次数	5