Paper Info
Title
Joint Offloading and Resource Allocation Optimization for Mobile Edge Computing.
Abstract
In this paper, we propose a game theoretic approach for joint offloading and resource allocation optimization (JORAO) problem in mobile edge computing (MEC) system. This study not only investigates offloading strategy, but also considers cloud and wireless resource allocation. Specially, the concern of the JORAO problem is to minimize the energy consumption and monetary cost from mobile terminals' perspective. However, the JORAO problem is non-convex and NP hard. Therefore, it is formulated as a JORAO game. The existence of Nash equilibrium (NE) is proved for it. To obtain NE, we also concentrate on cloud and wireless resource allocation algorithm (CWRAA), which is the sub-algorithm of the JORAO game. For the CWRAA, on one hand, we take consideration of OFDM sub-channels allocation and uplink power allocation in radio access networks (RAN). On the other hand, the computation resource allocation in MEC is studied. Simulation results show that the distributed JORAO game algorithm can nearly minimize the total cost of all mobile terminals (MTs) with low complexity. In addition, the energy consumption and completion time are less when the size of data becomes larger compared with existing algorithms.
Year
Venue
Keywords
2017
IEEE Global Communications Conference
Mobile edge computing,offloading strategy,resource allocation,game theory
Field
DocType
ISSN
Resource management,Mathematical optimization,Computer science,Server,Computer network,Mobile edge computing,Resource allocation,Nash equilibrium,Energy consumption,Orthogonal frequency-division multiplexing,Cloud computing
Conference
2334-0983
Citations 
PageRank 
References 
2
0.36
0
Authors
7
Name
Order
Citations
PageRank
Jing Zhang171.46
Weiwei Xia22814.30
Yueyue Zhang3207.77
Qian Zou420.36
Bonan Huang51019.87
Feng Yan6259.54
Lianfeng Shen751765.25