Cluster Content Caching: An Energy-Efficient Approach to Improve Quality of Service in Cloud Radio Access Networks

Abstract

In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantage of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower power cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

Boosting Fronthaul Capacity: Global Optimization of Power Sharing for Centralized Radio Access Network

“…Extensive efforts have been devoted to the enhancement of fronthaul capacity, including compression/quantization [9]- [11], quality of service (QoS) guarantee [12], [13], interference mitigation [14], [15], user/access link selection [16]- [18], as well as resource allocation and optimization [8], [19]- [21].…”

Information-centric mobile caching network frameworks and caching optimization: a survey

“…According to the C-RAN architecture, a cooperative caching framework is proposed in [36] based on Distributed Cloud Service Network architecture, in which several distributed cloudlets with local caches cooperate and share contents with each other. [37,38] proposes a cluster content caching structure in Edge Cloud-Radio Access Networks (EC-RANs), in which baseband signal processing and control functions are partially decentralized in the edge equipments, such as base stations and UEs with cache, and a common local content cache is deployed in BBU so that cache can be shared by the RRHs within the cluster. A fog computing based RAN (F-RAN) architecture is proposed in [39] which user plane and control plane are decoupled.…”

“…Caches can be placed in different network elements such as SBS, BBU pool and user devices based on various deployment strategies of C-RAN [37,130]. From the point view of management, by constructing a cloud computing platform above ICN and providing an interface for the interaction between ICN and cloud computing platform [131], malicious attacks to the data center network can be easily avoided due to security mechanism in Informationcentric mobile caching by ICN, and data recovery becomes extremely easy in the cloud over ICN.…”

Two Time-Scale Content Caching and User Association in 5G Heterogeneous Networks

“…Simulation results. We carry out the simulations under two different content request scenarios: 1) homogeneous content request distribution, i.e., ( ) = for all ∈ ℱ and for all ∈ ℒ, where follows Zipf distribution [16] for all contents, and 2) heterogeneous content request distribution, i.e., ( ) varies from location to location and content to content. We assume the Gaussian distribution with mean and variance 2 .…”