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A novel optimization scheme for caching in locality-aware P2P networks

机译:一种在位置感知的P2P网络中缓存的新型优化方案

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Deploying cache has been generally adopted by Internet service providers (ISPs) to mitigate P2P traffic in recent years. Most traditional caching algorithms are designed for locality-unaware P2P networks, which mainly consider the requested frequency of contents as the principle of caching policies. However, in more prevalent locality-aware conditions with biased neighbor-selection policies, the existing caching schemes can hardly optimize the situation. In this paper we show that, what need to be cached in locality-aware conditions are the contents that can not be well provided by local neighbors, rather than the contents which are requested most frequently. Therefore, states of local neighbors should be taken into consideration in caching policies. We first present a new model in which P2P cache and locality-aware neighbor selection work together. We focus on inter-ISP traffic and available bandwidth of users in order to benefit both ISPs and users. Based on the mathematical model, a novel caching algorithm is proposed which considers replacement and allocation policies together. According to trace-driven simulations, the proposed algorithm outperforms other two representative caching algorithms in various scenarios.
机译:近年来,Internet服务提供商(ISP)通常采用部署缓存来减轻P2P流量。大多数传统的缓存算法都是为不了解位置的P2P网络设计的,该算法主要将请求的内容频率视为缓存策略的原理。但是,在具有偏颇的邻居选择策略的更普遍的位置感知条件下,现有的缓存方案几乎无法优化这种情况。在本文中,我们表明,在位置感知条件下需要缓存的内容是本地邻居无法很好地提供的内容,而不是最经常请求的内容。因此,缓存策略中应考虑本地邻居的状态。我们首先提出一个新模型,其中P2P缓存和位置感知邻居选择一起工作。我们专注于ISP之间的流量和用户的可用带宽,以使ISP和用户都受益。在数学模型的基础上,提出了一种兼顾替换和分配策略的缓存算法。根据跟踪驱动的仿真,该算法在各种情况下均优于其他两种代表性的缓存算法。

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