Dynamic Resource Scheduling in Mobile Edge Cloud with Cloud Radio Access Network

Wang, Xinhou, Wang, Kezhi, Wu, Song, Di, Sheng, Jin, Hai, Yang, Kun and Ou, Shumao (2018) Dynamic Resource Scheduling in Mobile Edge Cloud with Cloud Radio Access Network. IEEE Transactions on Parallel and Distributed Systems. ISSN 1045-9219 (In Press)

[img]
Preview
Text
08353131.pdf - Accepted Version

Download (1MB) | Preview
Official URL: http://dx.doi.org/10.1109/TPDS.2018.2832124

Abstract

Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile edge cloud computing (MEC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile devices. But the power consumption has become skyrocketing for MSP and it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MEC separately while less work had considered the integration of C-RAN with MEC. In this paper, we present an unifying framework for the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MEC to maximize the profit of MSP. To achieve this objective, we formulate the resource scheduling issue as a stochastic problem and design a new optimization framework by using an extended Lyapunov technique. Specially, because the standard Lyapunov technique critically assumes that job requests have fixed lengths and can be finished within each decision making interval, it is not suitable for the dynamic situation where the mobile job requests have variable lengths. To solve this problem, we extend the standard Lyapunov technique and design the VariedLen algorithm to make online decisions in consecutive time for job requests with variable lengths. Our proposed algorithm can reach time average profit that is close to the optimum with a diminishing gap (1/V) for the MSP while still maintaining strong system stability and low congestion. With extensive simulations based on a real world trace, we demonstrate the efficacy and optimality of our proposed algorithm.

Item Type: Article
Uncontrolled Keywords: Cloud radio access network; Mobile edge computing; Power-performance tradeoff; Lyapunov optimization; Scheduling
Subjects: P900 Others in Mass Communications and Documentation
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 03 May 2018 12:14
Last Modified: 05 May 2018 10:03
URI: http://nrl.northumbria.ac.uk/id/eprint/34137

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence