Paper Info
Title
Dynamic Resource Provisioning for Energy Efficient Cloud Radio Access Networks
Abstract
Energy saving is critical for the cloud radio access networks (C-RANs), which are composed by massive radio access units (RAUs) and energy-intensive computing units (CUs) that host numerous virtual machines (VMs). We attempt to minimize the energy consumption of C-RANs, by leveraging the RAU sleep scheduling and VM consolidation strategies. We formulate the energy saving problem in C-RANs as a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">joint resource provisioning (JRP)</italic> problem of the RAUs and CUs. Since the active RAU selection is coupled with the VM consolidation, the JRP problem shares some similarities with a special bin-packing problem. In this problem, the number of items and the sizes of items are correlated and are both adjustable. No existing method can be used to solve this problem directly. Therefore, we propose an efficient low-complexity algorithm along with a context-aware strategy to dynamically select active RAUs and consolidate VMs to CUs. In this way, we can significantly reduce the energy consumption of C-RANs, while do not incur too much overhead due to VM migrations. Our proposed scheme is practical for a large-size network, and its effectiveness is demonstrated by the simulation results.
Year
DOI
Venue
2019
10.1109/TCC.2017.2715812
IEEE Transactions on Cloud Computing
Keywords
Field
DocType
Copper,Cloud computing,Energy consumption,Heuristic algorithms,Resource management,Dynamic scheduling,Radio access networks
Radio access,Virtual machine,Computer science,Efficient energy use,Scheduling (computing),Computer network,Provisioning,Real-time computing,Energy consumption,Cloud computing,Distributed computing
Journal
Volume
Issue
ISSN
7
4
21687161
Citations 
PageRank 
References 
2
0.37
0
Authors
5
Name
Order
Citations
PageRank
Yu Nuo1325.76
Song Zhaohui293.50
Du Hongwei334341.34
Huang Hejiao46615.07
Xiaohua Jia54609303.30