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An Adaptive Resource-based Probabilistic Search Algorithm For P2p Networks

机译:P2p网络中基于资源的自适应概率搜索算法

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A novel Adaptive Resource-based Probabilistic Search algorithm (ARPS) for P2P networks is proposed in this paper. ARPS introduces probabilistic forwarding for query messages according to the popularity of the resource being searched. A mechanism is introduced to estimate the popularity and adjust the forwarding probability accordingly such that a tradeoff between search performance and cost can be made. Using computer simulations, we compare the performance of ARPS with several other search algorithms. It is shown that ARPS performs well under various P2P scenarios. ARPS guarantees a success rate above a certain level under all circumstances, and enjoys high and popularity-invariant search success rate. Furthermore, ARPS adapts well to the variation of popularity, resulting in high efficiency and flexibility.
机译:提出了一种新颖的基于P2P网络的基于资源的自适应概率搜索算法(ARPS)。 ARPS根据要搜索的资源的普及程度为查询消息引入了概率转发。引入一种机制来估计受欢迎程度并相应地调整转发概率,以便可以在搜索性能和成本之间进行权衡。使用计算机模拟,我们将ARPS的性能与其他几种搜索算法进行了比较。结果表明,ARPS在各种P2P方案下均表现良好。在任何情况下,ARPS都能确保成功率超过一定水平,并且搜索成功率很高且不受流行程度的影响。此外,ARPS很好地适应了流行的变化,从而实现了高效率和灵活性。

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