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An Energy-Efficient Caching Strategy Based on Coordinated Caching for Green Content-Centric Network

机译:基于绿色内容中心网络协调缓存的节能缓存策略

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CCN (content-centric networking), a new network architecture, use content as centric to communicate to each other. In-network caching is a major feature of this promising architecture and takes advantage of in-network caching to low the latency requested from users and network transport load reduction. Thus, due to the wide in-network caching, CCNs have to cache much more replicas, which increases the caching energy. From the perspective of energy consumption and cost, the green CCNs find key factors influencing energy consumption. Under the situation of latest research of green CCNs, a autonomous regional network is choose as object of study and the nodes in network only needs locally available, caching and transport energy from cooperative caching group, content popularity and other information to make caching decision. The corresponding network energy consumption model is proposed, and a nonlinear programming formulates the network energy consumption problem. Furthermore an advanced genetic algorithm (GA) is used for solving nonlinear programming optimal solution. The results test and verify that the cooperative caching group exists an optimal caching depth for minimizing network energy consumption.
机译:CCN(以内容为中心的网络),新的网络架构,使用内容以中心为中心互相通信。网络内高速缓存是该有前途的架构的主要特点,并利用网络内高速缓存以低于用户和网络传输负载减少的延迟。因此,由于网络中的网络广泛缓存,CCNS必须高速缓存更多的副本,这增加了缓存能量。从能量消耗和成本的角度来看,绿色CCNS发现影响能源消耗的关键因素。在绿色CCNS的最新研究的情况下,自主区域网络是选择的研究对象,网络中的节点只需要来自合作缓存组,内容人气和其他信息的本地可用,缓存和传输能量来进行缓存决策。提出了相应的网络能量消耗模型,并且非线性编程制定了网络能量消耗问题。此外,先进的遗传算法(GA)用于求解非线性编程最佳解决方案。结果测试并验证了合作缓存组是否存在最佳缓存深度,以最大限度地降低网络能耗。

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