Optimal cache placement for an academic backbone network

Q4 Decision Sciences
Than Nguyen Hau, Naonori Kakimura, K. Kawarabayashi, Yusuke Kobayashi, Tatsuya Matsuoka, Yu Yokoi
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引用次数: 1

Abstract

Deploying caches on a network is an effective way to reduce the amount of data transmitted in a network. Recently, in an academic backbone network such as SINET (the Science Information Network) in Japan, the amount of transmitted data has signi(cid:12)cantly increased. It is desired to design an efficient mechanism to allocate caches in an optimal way. In this paper, we begin by formulating a discrete optimization model to (cid:12)nd a cache allocation that minimizes the total transmission cost. We then design two efficient algorithms to solve our proposed model. The (cid:12)rst one makes use of the fact that a backbone network has small treewidth. The algorithm runs in polynomial time when the number of items is (cid:12)xed and a graph has a bounded treewidth. The other one reduces the problem to the minimum-cost (cid:13)ow problem under the practical assumption that each item has at most one copy. This yields a polynomial-time combinatorial algorithm. Our numerical experiments on the real SINET network show that our algorithms can solve the cache placement problem efficiently in practice.
学术骨干网络的最佳缓存放置
在网络上部署缓存是减少网络中传输数据量的有效方法。最近,在诸如日本的SINET(科学信息网络)之类的学术骨干网络中,传输的数据量显著增加(cid:12)。希望设计一种有效的机制来以最佳方式分配缓存。在本文中,我们首先建立了一个离散优化模型,以(cid:12)确定最大限度地降低总传输成本的缓存分配。然后,我们设计了两种有效的算法来解决我们提出的模型。第一个(cid:12)利用了骨干网络具有较小树宽的事实。当项数为(cid:12)x并且图具有有界树宽时,该算法在多项式时间内运行。另一种是在每个项目最多有一个副本的实际假设下,将问题简化为最小成本(cid:13)ow问题。这产生了一个多项式时间组合算法。我们在实际SINET网络上的数值实验表明,我们的算法在实践中可以有效地解决缓存放置问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of the Operations Research Society of Japan
Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学
CiteScore
0.70
自引率
0.00%
发文量
12
审稿时长
12 months
期刊介绍: The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.
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