A cross-layer green information-centric networking design toward the energy internet

Abstract

To address the energy-efficiency issue in Information-Centric Networking (ICN), this article proposes a novel Green ICN design, which adapts the power consumption of network nodes to the optimized utilization level proportionally. By learning over the consumers’ interactive data traffic pattern/behavior, we introduce a new concept of cross-layer power adaption conducted through dynamically adjusting link rate corresponding to content popularity to reduce the wasteful power consumption of Content Routers (CRs). We also develop a controlling policy for each content provider to map its status to the most suitable operating mode to diminish power consumption. Moreover, we propose a smart Selective Caching Scheme (SCS) so that the caching portion in a CR’s cache memory is adjusted according to content popularity and available spaces of two customized content cache spaces, namely hot and cold caching queues, for storing popular and unpopular content objects. This scheme can further decrease the power from caching since it is diminished when the traffic load is reduced via the proposed CRs’ adaptive mechanism. The evaluation results with practical insights in several distinct scenarios show that the proposal can provide considerably higher energy efficiency and network performance at the same time, typically achieving at least 20% power-saving with a higher hop reduction ratio, compared to existing Internet designs with relevant state-of-the-art caching strategies.