Nearly Optimal Algorithm for Placing Content-Replication in Elastic Optical Networks

T. Miyamura, A. Misawa
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Abstract

We propose a network-aware light-weight content-replication placement algorithm (NetLCP) for efficient large-scale content distribution in elastic optical networks. We previously proposed an architecture of information-centric elastic optical transport networks called i-CEON for efficient large-scale content delivery. In i-CEON, we deploy in-network cache functions (ICFs) to reduce redundant use of network resources. The key lies in how to adequately place replicated content in ICFs so as to improve the efficiency of optical paths. In our previous work, we formulated the joint optimization of such a problem as mixed integer linear programming. Though the previous method always finds the optimal solutions, it fails to ensure network scalability and quick responsiveness. To overcome this issue, we develop a nearly optimal heuristic algorithm called NetLCP that improves efficiency of network resources with practical computational overhead. We conducted intensive numerical experiments and demonstrated that NetLCP always found nearly optimal solutions and indicated fewer than 10% of approximation errors compared with the optimal solutions.
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弹性光网络中放置内容复制的近最优算法
我们提出了一种网络感知的轻量级内容复制放置算法(NetLCP),用于弹性光网络中高效的大规模内容分发。我们之前提出了一种以信息为中心的弹性光传输网络架构,称为i-CEON,用于高效的大规模内容传输。在i-CEON中,我们部署了网络内缓存功能(ICFs)来减少网络资源的冗余使用。关键在于如何在ICFs中适当地放置复制内容,从而提高光路的效率。在之前的工作中,我们给出了一类混合整数线性规划问题的联合优化。前一种方法虽然总能找到最优解,但不能保证网络的可扩展性和快速响应。为了克服这个问题,我们开发了一种近乎最优的启发式算法,称为NetLCP,它在实际计算开销的情况下提高了网络资源的效率。我们进行了大量的数值实验,证明了NetLCP总是找到接近最优解,并且与最优解相比,其近似误差小于10%。
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