A distributed energy consumption optimization algorithm for content-centric networks via dual decomposition

Chao Fang, F. Yu, Tao Huang, Jiang Liu, Yun-jie Liu
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引用次数: 4

Abstract

Due to the in-network caching capability, Content-Centric Networking (CCN) has emerged as one of the most promising architectures for the diffusion of contents over the Internet. Most existing works on CCN focus on network resource utilization, and the energy efficiency aspect is largely ignored. In this paper, we formulate the energy consumption issue as a Mixed Integer Linear Programming (MILP) problem, and propose a centralized solution via spanning tree heuristic and a fully distributed energy consumption optimization algorithm via dual decomposition (DD) to solve the problem for CCN. The dual decomposition method transforms the centralized energy consumption optimization problem into the router status, link status, and link flow subproblems. Simulation results reveal that the proposed scheme exhibits a fast convergence speed, and achieves superior energy efficiency compared to other widely used schemes in CCN.
基于对偶分解的内容中心网络分布式能耗优化算法
由于具有网络内缓存功能,以内容为中心的网络(Content-Centric Networking, CCN)已成为在Internet上传播内容的最有前途的体系结构之一。现有的CCN研究大多集中在网络资源利用方面,而在很大程度上忽略了网络的能效方面。本文将能源消耗问题表述为混合整数线性规划(MILP)问题,并提出了一种基于生成树启发式的集中式解决方案和一种基于对偶分解(DD)的全分布式能源消耗优化算法来解决CCN问题。对重分解方法将集中能耗优化问题分解为路由器状态、链路状态和链路流子问题。仿真结果表明,该方案具有较快的收敛速度,并且与CCN中广泛使用的其他方案相比具有优越的能效。
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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