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Joint Energy Minimization and Resource Allocation in C-RAN with Mobile Cloud

Wang, Kezhi, Yang, Kun, Magurawalage, Chathura, S (2016) Joint Energy Minimization and Resource Allocation in C-RAN with Mobile Cloud. IEEE file. 9 kB. Located at: IEEE Transactions on Cloud Computing (Volume:PP , Issue: 99 ). 10.1109/TCC.2016.2522439. (doi:10.1109/TCC.2016.2522439) (KAR id:56944)

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Official URL
http://dx.doi.org/10.1109/TCC.2016.2522439

Abstract

Cloud radio access network (C-RAN) has emerged as a potential candidate of the next generation access network technology to address the increasing mobile traffic, while mobile cloud computing (MCC) offers a prospective solution to the resource-limited mobile user in executing computation intensive tasks. Taking full advantages of above two cloud-based techniques, C-RAN with MCC are presented in this paper to enhance both performance and energy efficiencies. In particular, this paper studies the joint energy minimization and resource allocation in C-RAN with MCC under the time constraints of the given tasks. We first review the energy and time model of the computation and communication. Then, we formulate the joint energy minimization into a non-convex optimization with the constraints of task executing time, transmitting power, computation capacity and fronthaul data rates. This non-convex optimization is then reformulated into an equivalent convex problem based on weighted minimum mean square error (WMMSE). The iterative algorithm is finally given to deal with the joint resource allocation in C-RAN with mobile cloud. Simulation results confirm that the proposed energy minimization and resource allocation solution can improve the system performance and save energy.

Item Type: Datasets / databases
DOI/Identification number: 10.1109/TCC.2016.2522439
Projects: [UNSPECIFIED] Intelligent converged network consolidating radio and optical access around user equipment
Uncontrolled keywords: C-RAN, Joint Energy Minimization, Mobile Cloud Computing, Resource Allocation
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK5101 Telecommunications > TK5103.59 Optical communications
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Kornelia Jumel
Date Deposited: 23 Aug 2016 14:06 UTC
Last Modified: 16 Feb 2021 13:36 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/56944 (The current URI for this page, for reference purposes)
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