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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >On Cost-Driven Collaborative Data Caching: A New Model Approach
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On Cost-Driven Collaborative Data Caching: A New Model Approach

机译:成本驱动的协作数据缓存:一种新的模型方法

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摘要

In this paper we consider a new caching model that enables data sharing for network services in a cost-effective way. The proposed caching algorithms are characterized by using monetary cost and access information to control the cache replacements, instead of exploiting capacity-oriented strategies as in traditional approaches. In particular, given a stream of requests to a shared data item with respect to a homogeneous cost model, we first propose a fast off-line algorithm using dynamic programming techniques, which can generate an optimal schedule within O(mn) time-space complexity by using cache, migration as well as replication to serve a n-length request sequence in a m-node network, substantially improving the previous results. Furthermore, we also study the online form of this problem, and present an 3-competitive online algorithm by leveraging an idea of anticipatory caching. The algorithm can serve an online request in constant time and is space efficient in O(m) as well, rendering it more practical in reality. We evaluate our algorithms, together with some variants, by conducting extensive simulation studies. Our results show that the optimal cost of the off-line algorithm is changed in a parabolic form as the ratio of caching cost to transfer cost is increased, and the online algorithm is less than 2 times worse in most cases than its optimal off-line counterpart.
机译:在本文中,我们考虑了一种新的缓存模型,该模型能够以经济高效的方式实现网络服务的数据共享。所提出的缓存算法的特征在于使用金钱成本和访问信息来控制缓存替换,而不是像传统方法那样利用面向容量的策略。特别是,对于同质成本模型,考虑到对共享数据项的请求流,我们首先提出一种使用动态编程技术的快速离线算法,该算法可以在O(mn)时空复杂度内生成最佳调度通过使用高速缓存,迁移以及复制来为m节点网络中的n长度请求序列提供服务,从而大大改善了先前的结果。此外,我们还研究了此问题的在线形式,并通过利用预期缓存的思想提出了一种3竞争在线算法。该算法可以在恒定时间内满足在线请求,并且在O(m)方面也具有空间效率,因此在现实中更加实用。通过进行广泛的仿真研究,我们评估了我们的算法以及一些变体。我们的结果表明,随着缓存成本与传输成本之比的增加,离线算法的最优成本以抛物线形式变化,并且在大多数情况下,在线算法比其最优离线的性能差不到2倍。对方。

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