Probabilistic prediction of peers' performance in P2P networks
Probabilistic prediction of peers' performance in P2P networks
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DOI：
10.1016/j.engappai.2005.06.001
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发表时间：
2005-10
期刊：
影响因子：
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通讯作者：
Zoran Despotovic;K. Aberer
中科院分区：
文献类型：
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作者：
Zoran Despotovic;K. Aberer
在P2P网络社区中，通过管理节点的声誉来鼓励用户的可信行为的问题近年来引起了广泛的关注。然而，大多数提出的解决方案表现出以下两个问题：巨大的实现开销和不明确的信任相关的模型语义。本文表明，一个简单的概率技术，即最大似然估计，可以大大减少这两个问题时，采用的反馈聚合策略。我们评估的技术在三个设置相关的P2P网络的应用程序，并表明它在所有这些都表现良好。因此，不需要对反馈进行复杂的探索。相反，简单、直观和有效的概率估计方法就足够了。
The problem of encouraging trustworthy behavior in P2P online communities by managing peers’ reputations has drawn a lot of attention recently. However, most of the proposed solutions exhibit the following two problems: huge implementation overhead and unclear trust related model semantics. This paper shows that a simple probabilistic technique, maximum likelihood estimation namely, can reduce these two problems substantially when employed as the feedback aggregation strategy. We evaluate the technique in three settings relevant for applications of P2P networks and show that it performs well in all of them. Thus, no complex exploration of the feedback is necessary. Instead, simple, intuitive and efficient probabilistic estimation methods suffice.