Dynamic resource scheduling in cloud radio access network with mobile cloud computing

Wang, Xinhou, Wang, Kezhi, Wu, Song, Di, Sheng, Yang, Kun and Jin, Hai (2016) Dynamic resource scheduling in cloud radio access network with mobile cloud computing. In: 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS). IEEE, p. 7590428. ISBN 978-1-5090-2635-7

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/IWQoS.2016.7590428


Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile cloud computing (MCC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile users' devices to provide better quality of service (QoS). But the power consumption has become skyrocketing for MSP as it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MCC separately while less work had considered the integration of C-RAN with MCC. In this paper, we present a unifying framework for optimizing the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MCC to minimize the power consumption of MSP while still guaranteeing the QoS for mobile users. Our objective is to maximize the profit of MSP. To achieve this objective, we first formulate the resource scheduling issue as a stochastic problem and then propose a Resource onlIne sCHeduling (RICH) algorithm using Lyapunov optimization technique to approach a time average profit that is close to the optimum with a diminishing gap (1/V) for MSP while still maintaining strong system stability and low congestion to guarantee the QoS for mobile users. With extensive simulations, we demonstrate that the profit of RICH algorithm is 3.3× (18.4×) higher than that of active (random) algorithm.

Item Type: Book Section
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 25 Sep 2018 15:25
Last Modified: 11 Oct 2019 19:15
URI: http://nrl.northumbria.ac.uk/id/eprint/35902

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