Title
Joint Multi-User Computation Offloading and Data Caching for Hybrid Mobile Cloud/Edge Computing
Abstract
In this paper, we investigate a hybrid mobile cloud/edge computing system with coexistence of centralized cloud and mobile edge computing, which enables computation offloading and data caching to improve the performance of users. Computation offloading and data caching decisions are jointly optimized to minimize the total execution delay at the mobile user side, while satisfying the constrains in terms of the maximum tolerable energy consumption of each user, the computation capability of each MEC server, and the cache capacity of each access point (AP). The formulated problem is non-convex and challenging because of the highly coupled decision variables. To address such an untractable problem, we first transform the original problem into an equivalent convex one by McCormick envelopes and introducing auxiliary variables. To the end, we propose a distributed algorithm based on the alternating direction method of multipliers (ADMM), which can achieve near optimal computation offloading and data caching decisions. The proposed algorithm has lower computational complexity compared to the centralized algorithm. Simulation results are presented to verify that the proposed algorithm can effectively reduce computing delay for end users while ensuring the performance of each user.
Year
DOI
Venue
2019
10.1109/TVT.2019.2942334
IEEE Transactions on Vehicular Technology
Keywords
Field
DocType
Servers,Cloud computing,Task analysis,Computational modeling,Delays,Optimization,Uplink
Edge computing,Computer science,Server,Computer network,Computation offloading,Mobile edge computing,Distributed algorithm,Computation,Distributed computing,Cloud computing,Computational complexity theory
Journal
Volume
Issue
ISSN
68
11
0018-9545
Citations 
PageRank 
References 
10
0.49
0
Authors
5
Name
Order
Citations
PageRank
Xiaolong Yang115733.68
Zesong Fei269986.33
Jianchao Zheng322316.21
Ning Zhang474459.81
Alagan Anpalagan51263125.52