An energy-efficient caching strategy based on coordinated caching for green content-centric network

Abstract

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.