JOURNAL ARTICLE

Energy-Efficient Joint Offloading and Wireless Resource Allocation Strategy in Multi-MEC Server Systems

Abstract

Mobile edge computing (MEC) is an emerging paradigm that mobile devices can offload the computation-intensive or latency-critical tasks to the nearby MEC servers, so as to save energy and extend battery life. Unlike the cloud server, MEC server is a small-scale data center deployed at a wireless access point, thus it is highly sensitive to both radio and computing resource. In this paper, we consider an Orthogonal Frequency-Division Multiplexing Access (OFDMA) based multi-user and multi-MEC-server system, where the task offloading strategies and wireless resources allocation are jointly investigated. Aiming at minimizing the total energy consumption, we propose the joint offloading and resource allocation strategy for latency- critical applications. Through the bi-level optimization approach, the original NP-hard problem is decoupled into the lower-level problem seeking for the allocation of power and subcarrier and the upper-level task offloading problem. Simulation results show that the proposed algorithm achieves excellent performance in energy saving and successful offloading probability (SOP) in comparison with conventional schemes. © 2018 IEEE.

Keywords:
Computer science Mobile edge computing Server Computer network Resource allocation Wireless Cloud computing Computation offloading Energy consumption Latency (audio) Distributed computing Edge computing Operating system Engineering

Metrics

133
Cited By
15.92
FWCI (Field Weighted Citation Impact)
21
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
IoT Networks and Protocols
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Age of Information Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
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