虚拟计算环境中基于重复博弈的惩罚激励机制.pdf

文档介绍：ISSN 1000-9825, CODEN RUXUEW E-mail: ******@iscas.
Journal of Software, , , December 2010, −3055
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虚拟计算环境中基于重复博弈的惩罚激励机制
桂春梅+, 蹇强, 王怀民, 吴泉源
(国防科学技术大学计算机学院,湖南长沙 410073)
Repeated Game Theory Based Penalty-Incentive Mechanism in -Based Virtual
Computing Environment
GUI Chun-Mei+, JIAN Qiang, WANG Huai-Min, WU Quan-Yuan
(School puter Science, National University of Defense Technology, Changsha 410073, China)
+ Corresponding author: E-mail: plantsperfum@
Gui CM, Jian Q, Wang HM, Wu QY. Repeated game theory based penalty-incentive mechanism in -
based puting environment. Journal of Software, 2010,21(12):3042−3055. /
1000-9825/
Abstract: In order to construct a puting platform for the next , there needs to be
normalizing and promoting of autonomic elements in order to have them collaborate actively with on another. A
novel penalty-incentive mechanism, named PETrust, based on a repeated game theory, is given in this paper. This
paper aims at providing a set of mechanisms, which the behavior of autonomic elements is normalized and is
promoted to take the expected strategy. PETrust adjusts the degree of penalty by changing the reputation status.
Theoretical analysis and simulation results show that PETrust can distinguish the different features of behavior,
effectively, can punish and stifle malicious behavior, can improve the system’s entire efficiency, can stimulate
autonomic elements’ honest trade enthusiasm, and can provide a better capacity of resisting collusive deception.
Furthermore, PETrust presents both low plexity and few incurred packets, which is favourable for
engineering deployment and implementation.
Key words: autonomic element; reputation; collaboration; behavior criterion; penalty and incentive
摘要: 如何促进网络中自主元素自觉规范行为、积极有序协作从而形成“可信的计算平台”是下一代互联网