Abstract

With the development of Internet of Things, the mobile edge computing has become a promising technology for real-time communications. This paper investigates a mobile edge computing system that consists of an access point integrated with a mobile edge computing server, multiple mobile stations, and a malicious eavesdropper. By offloading part of the computing tasks to the mobile edge computing server, the energy consumption of mobile stations can be reduced significantly and the lifetime is prolonged as well. Moreover, the physical layer security is an effective technique to guarantee the secure transmission of the offloading data. Based on the proposed system model, we formulate an optimization problem to minimize the energy consumption of the system by jointly optimizing the allocations of local computing tasks, local central processor's frequency, offloading power, and offloading timeslots. A difference of convex algorithm based scheme is proposed to solve the problem. The performance of the proposed scheme is superior to the benchmark schemes, which is demonstrated by simulation results.

Keywords:
Computer science Mobile edge computing Edge computing Benchmark (surveying) Enhanced Data Rates for GSM Evolution Mobile computing Energy consumption Computer network Distributed computing Mobile device Server Operating system Telecommunications

Metrics

7
Cited By
1.16
FWCI (Field Weighted Citation Impact)
18
Refs
0.80
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
Age of Information Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
IoT Networks and Protocols
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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