网格计算中的增量信任

Michael Brinklov, Robin Sharp
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引用次数: 19

摘要

本文对大型分布式系统中处理行为信任的一些增量信任算法和信誉算法进行了比较仿真研究。考虑了两种类型的信誉算法(基于离散和贝叶斯评级评价)和两种直接信任与信誉相结合的方法(基于模糊逻辑的组合和离散组合)。从对行为变化的响应能力和在网格系统环境中为算法找到合适参数的难易程度的角度来评估这些方法的各种组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incremental Trust in Grid Computing
This paper describes a comparative simulation study of some incremental trust and reputation algorithms for handling behavioural trust in large distributed systems. Two types of reputation algorithm (based on discrete and Bayesian evaluation of ratings) and two ways of combining direct trust and reputation (discrete combination and combination based on fuzzy logic) are considered. The various combinations of these methods are evaluated from the point of view of their ability to respond to changes in behaviour and the ease with which suitable parameters for the algorithms can be found in the context of Grid systems.
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