A review on green caching strategies for next generation communication networks

© 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching

A Cache Placement Strategy with Energy Consumption Optimization in Information-Centric Networking

With the rapid development of cloud computing, big data, and Internet of Things, Information-Centric Networking (ICN) has become a novel hotspot in the field of future Internet architecture, and new problems have appeared. In particular, more researchers consider information naming, delivery, mobility, and security in ICN. In this paper, we mainly focus on the cache placement strategy and network performance of ICN, and propose a cache placement strategy with energy consumption optimization. In order to optimize the energy consumption of the ICN, the best cache placement node is selected from the view of users. First of all, the distance sequence of different nodes arriving at each user is obtained in terms of detection results of network distribution channels, and the corresponding energy consumption of information distribution is obtained from the distance sequence. Secondly, the reward function of the cache node is derived using two factors of energy consumption, which includes the additional energy consumed by the change of the cache node and the energy consumption of the content distribution. Finally, we construct the optimal stopping theory problem to solve the maximum expected energy saving. In simulations, we give the comparison results of energy savings, caching benefit, and delivery success rate. The results show that the strategy proposed by this paper has higher delivery success rate and lower energy consumption than other strategies