机会网络自私节点的Bertrand博弈与激励机制研究

doi:10.3778/j.issn.1002-8331.1902-0214

计算机工程与应用 ›› 2020, Vol. 56 ›› Issue (13): 106-113.DOI: 10.3778/j.issn.1002-8331.1902-0214

机会网络自私节点的Bertrand博弈与激励机制研究

吴青，曾锋

中南大学计算机学院，长沙 410000

出版日期:2020-07-01 发布日期:2020-07-02

Research on Bertrand Game and Incentive Mechanism for Selfish Nodes in Opportunistic Networks

WU Qing, ZENG Feng

School of Computer Science and Engineering, Central South University, Changsha 410000, China

Online:2020-07-01 Published:2020-07-02

摘要/Abstract

摘要：

在真实的网络环境中，很多节点可能是自私的，它们不愿意牺牲自己的资源为其他节点转发消息。针对这种情况，提出一种基于博弈论的激励机制，可以激励节点与其他节点相互合作。该机制为二阶段激励，激励节点接收消息以协助其他节点转发，同时激励节点转发更多的消息。把源节点与中继节点之间的竞争与合作模型化为Bertrand（伯特兰德）博弈，定义了源节点和中继节点的效用函数。求解了源节点的最佳定价策略和中继节点最佳的转发计划，验证了源节点与中继节点之间存在唯一的纳什均衡。模拟仿真结果表明提出的激励机制能够鼓励自私节点参与合作，能提高路由算法的传递率，同时降低了消息传递延迟。与基于声誉的激励机制相比，所提激励机制能使消息传递成功率提高31.4%、平均时延降低9.7%。

关键词: 博弈论, 二阶段激励, Bertrand博弈, 纳什均衡

Abstract:

In a real environment, many nodes may be selfish and unwilling to sacrifice their own resources to forward messages for other nodes. In this case, an incentive mechanism based on game theory to encourage the cooperation between nodes is proposed. This incentive provides two-stage incentives to nodes, which incentives node receives the message to assist other nodes to forward, while motivating the node to forward more messages. It models the cooperation between the source and the relay node as Bertrand game, and the utility functions of the source and the relay node are defined. It solves the best pricing scheme for the source node and the best forwarding plan for the relay node, and the Nash equilibrium is existed and unique between source node and relay node. The simulation results show that the proposed incentive mechanism can encourage the cooperation between selfish nodes, and improve the performance of routing algorithm in terms of delivery rate and delay. Compared with reputation-based incentive mechanism, the proposed mechanism has the success rate of message transmission increased by 31.4% and average delay decreased by 9.7%.

Key words: game theory , two-stage incentives, Bertrand game, Nash equilibrium

吴青，曾锋. 机会网络自私节点的Bertrand博弈与激励机制研究[J]. 计算机工程与应用, 2020, 56(13): 106-113.

WU Qing, ZENG Feng. Research on Bertrand Game and Incentive Mechanism for Selfish Nodes in Opportunistic Networks[J]. Computer Engineering and Applications, 2020, 56(13): 106-113.

[1]	王晋宇，杨海涛，李高源，张长弓，冯博迪. 生成对抗网络及其图像处理应用研究进展[J]. 计算机工程与应用, 2021, 57(8): 26-35.
[2]	王军，曹雷，陈希亮，赖俊，章乐贵. 多智能体博弈强化学习研究综述[J]. 计算机工程与应用, 2021, 57(21): 1-13.
[3]	刘根旺，周颖，张磊，康增信. 基于博弈论的人员疏散演化研究[J]. 计算机工程与应用, 2020, 56(8): 49-54.
[4]	王妍，马秀荣，单云龙. Shapley值的LTE系统下行QoS感知资源调度[J]. 计算机工程与应用, 2020, 56(4): 76-81.
[5]	徐齐利. 讨价还价博弈均衡出价策略的算法设计[J]. 计算机工程与应用, 2020, 56(21): 170-175.
[6]	蒋凌燕1，王晓光2. 物联网技术下重复质押风险的防范[J]. 计算机工程与应用, 2019, 55(9): 223-229.
[7]	陈佳，游晓明，刘升，李娟. 结合信息熵的多种群博弈蚁群算法[J]. 计算机工程与应用, 2019, 55(16): 170-178.
[8]	柴艳妹，韩文英，王坚，王友卫. 博弈选择模型在步态识别中的应用研究[J]. 计算机工程与应用, 2018, 54(19): 26-33.
[9]	陈禹1，冯翔1，2，虞慧群1. 改进型帝国竞争模型算法的研究[J]. 计算机工程与应用, 2018, 54(12): 206-213.
[10]	王莉莉1，陈国彬1，张广泉2，3. 认知无线电网络中基于公平性的功率控制方案[J]. 计算机工程与应用, 2017, 53(3): 144-148.
[11]	孙楚，赵辉，王骁飞，魏政磊. 区间数决策在无人机攻防博弈中的应用[J]. 计算机工程与应用, 2017, 53(15): 170-175.
[12]	陈明1，文颖1，谭涛2. WSN中基于MDP与博弈论的入侵检测系统[J]. 计算机工程与应用, 2015, 51(9): 117-121.
[13]	张健，王晋东，张恒巍. 静态贝叶斯博弈在信息系统风险分析中的应用[J]. 计算机工程与应用, 2015, 51(11): 76-82.
[14]	徐昕1，2，虞慧群1，黄骏虎1. 基于Petri网的CPS系统安全量化分析模型[J]. 计算机工程与应用, 2014, 50(3): 82-88.
[15]	陈军，肖明波. 基于非合作博弈的改进型认知无线电功控算法[J]. 计算机工程与应用, 2014, 50(18): 220-225.

机会网络自私节点的Bertrand博弈与激励机制研究

Research on Bertrand Game and Incentive Mechanism for Selfish Nodes in Opportunistic Networks

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics