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Distributed Caching Independent of the Network Size

机译:与网络大小无关的分布式缓存

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摘要

We consider distributed caching strategies for networks in a model that takes in addition to remote accesses also local accesses into account. The goal is to minimize the congestion while obeying memory capacity constraints in the network. The on-line strategies are evaluated in a competitive analysis in which their costs are compared with the cost of an optimal off-line strategy. Previous results either depend on the network size or assume that the on-line strategies have increased memory capacity constraints in comparison to an optimal off-line strategy. Our main result is a strategy for complete networks. For each node v, we are given memory capacity m(v) and load d(v) for a remote access. The load for a local access is one. Note that, for uniform memory capacity TO and uniform load d for a remote access, the competitive ratio simplifies to O(log(min(d,m))). In addition, we give a lower bound which shows that the strategy is optimal in the uniform case. Furthermore, the impact of typical applications, i.e., those which exhibit significant locality of reference, is investigated. Finally, an universal caching strategy for arbitrary networks is presented which is based on a simulation of the strategy for complete networks. We show that the competitive ratio of this strategy depends primary on the routing capacity and degree of the network. Examples of networks, including Cayley and edge symmetric networks, are given for which the universal caching strategy achieves efficient competitive ratios.
机译:我们在模型中考虑了网络的分布式缓存策略,该模型除了要考虑远程访问之外还要考虑本地访问。目的是在遵守网络中内存容量限制的同时将拥塞降到最低。在线策略在竞争性分析中进行评估,将其成本与最佳离线策略的成本进行比较。先前的结果取决于网络规模,或者假定与最佳的离线策略相比,在线策略具有增加的存储容量约束。我们的主要结果是制定完整网络的策略。对于每个节点v,我们将获得内存容量m(v)和负载d(v),以进行远程访问。本地访问的负载是一个。注意,对于用于远程访问的统一存储容量TO和统一负载d,竞争比率简化为O(log(min(d,m)))。另外,我们给出一个下界,表明该策略在统一情况下是最佳的。此外,还研究了典型应用的影响,即那些表现出很大参考区域的应用。最后,基于对完整网络策略的仿真,提出了一种用于任意网络的通用缓存策略。我们表明,该策略的竞争比主要取决于路由容量和网络的程度。给出了包括Cayley和边缘对称网络在内的网络示例,其通用缓存策略可实现有效的竞争比率。

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