Decentralised trust-management inspired by ant pheromones

被引:0
|
作者
Edenhofer S. [1 ]
Tomforde S. [2 ]
Fischer D. [1 ]
Hähner J. [1 ]
Menzel F. [3 ]
Von Mammen S. [1 ]
机构
[1] Organic Computing Group, University of Augsburg, Eichleitnerstr. 30, Augsburg
[2] Intelligent Embedded Systems Group, University of Kassel, Wilhelmshoher Allee 73, Kassel
[3] Department of Evolutionary Biology, Institute of Zoology, University of Mainz, Johannes-von-Muller-Weg 6, Mainz
来源
Edenhofer, Sarah (sarah.edenhofer@informatik.uni-augsburg.de) | 1600年 / Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland卷 / 07期
关键词
Ant algorithms; Asymmetric encryption; Computing grid systems; Distributed verification; MAS; Multi-agent systems; Organic computing; Pheromones; Trust;
D O I
10.1504/IJMNDI.2017.082804
中图分类号
学科分类号
摘要
Computational trust is increasingly utilised to select interaction partners in open technical systems consisting of heterogeneous, autonomous agents. Current approaches rely on centralised elements for managing trust ratings (i.e. control and provide access to aggregated ratings). Consider a grid computing application as illustrating example: agents share their computing resources and cooperate in terms of processing computing jobs. These agents are free to join and leave, and they decide on their own with whom to interact. The impact of malicious or uncooperative agents can be countered by only cooperating with agents that have shown to be benevolent: trust relationships are established. Typically, this requires a centralised data-base storing information about past interactions and their outcome. In this article, we propose a novel, decentralised trust mechanism inspired by the nestmate recognition system in ants. More precisely, the concept of recognition pheromones, which stick to the agents and cannot be removed or counterfeit, is turned into algorithmic logic and interaction protocols. We demonstrate the potential benefit by using simulations of the grid scenario. Copyright © 2017 Inderscience Enterprises Ltd.
引用
收藏
页码:46 / 55
页数:9
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