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An update-based step-wise optimal cache replacement for wireless data access

机译:用于无线数据访问的基于更新的逐步最佳缓存替换

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Many network applications requires access to most up-to-date information. An update event makes the corresponding cached data item obsolete, and cache hits due to obsolete data items become simply useless to those applications. Frequently accessed but infrequently updated data items should get higher preference while caching, and infrequently accessed but frequently updated items should have lower preference. Such items may not be cached at all or should be evicted from the cache to accommodate items with higher preference. In wireless networks, remote data access is typically more expensive than in wired networks. Hence, an efficient caching scheme considers both data access and update patterns can better reduce data transmissions in wireless networks. In this paper, we propose a step-wise optimal update-based replacement policy, called the Update-based Step-wise Optimal {USO) policy, for wireless data networks to optimize transmission cost by increasing effective hit ratio. Our cache replacement policy is based on the idea of giving preference to frequently accessed but infrequently updated data, and is supported by an analytical model with quantitative analysis. We also present results from our extensive simulations. We demonstrate that (1) the analytical model is validated by the simulation results and (2) the proposed scheme outperforms the Least Frequently Used (LFU) scheme in terms of effective hit ratio and communication cost.
机译:许多网络应用程序需要访问最新信息。更新事件会使相应的缓存数据项过时,并且由于过时的数据项而导致的缓存命中对这些应用程序变得毫无用处。经常访问但不经常更新的数据项在缓存时应具有较高的优先级,而不经常访问但经常更新的数据项应具有较低的优先级。此类项目可能根本不会被缓存,或者应从缓存中逐出以容纳具有较高优先级的项目。在无线网络中,远程数据访问通常比在有线网络中更昂贵。因此,一种有效的缓存方案考虑了数据访问和更新模式都可以更好地减少无线网络中的数据传输。在本文中,我们为无线数据网络提出了一种基于逐步更新的逐步最佳替换策略,称为基于更新的逐步最佳(USO)策略,以通过增加有效命中率来优化传输成本。我们的缓存替换策略基于优先访问频繁但不经常更新的数据的思想,并得到带有定量分析的分析模型的支持。我们还将介绍我们广泛的模拟结果。我们证明(1)仿真模型验证了该分析模型,并且(2)在有效命中率和通信成本方面,所提出的方案优于最不常用(LFU)方案。

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