Resource allocation and computation offloading with data security for mobile edge computing

被引:92
|
作者
Elgendy, Ibrahim A. [1 ]
Zhang, Weizhe [1 ,2 ]
Tian, Yu-Chu [3 ]
Li, Keqin [4 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China
[2] Peng Cheng Lab, Shenzhen, Guangdong, Peoples R China
[3] QUT, Sch Elect Engn & Comp Sci, Brisbane, Qld, Australia
[4] SUNY Coll New Paltz, Dept Comp Sci, New Paltz, NY 12561 USA
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2019年 / 100卷
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
Computation offloading; Internet of Things (IoT); Mobile-edge computing; Optimization; Security; IOT; OPTIMIZATION;
D O I
10.1016/j.future.2019.05.037
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
With the considerable growth of mobile users (MUs) and IoT devices, complex applications and multimedia services are rapidly increasing, thereby requiring additional computations and high data communication. However, these devices are still resource-constrained with limited computation power and energy. Furthermore, security is considered a critical issue for sensitive information communication. This study presents a multiuser resource allocation and computation offloading model with data security to address the limitations of such devices. First, the computation and radio resources are jointly considered for multiuser scenarios to guarantee the efficient utilization of shared resources. In addition, an AES cryptographic technique is introduced as a security layer to protect sensitive information from cyber-attacks. Furthermore, an integrated model, which jointly considers security, computation offloading, and resource allocation, is formulated to minimize time and energy consumption of the entire system. Finally, an offloading algorithm is developed with detailed processes to determine the optimal computation offloading decision for MUs. Simulation results show that our model and algorithm can significantly improve the performance of the entire system compared with local execution and full offloading schemes. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:531 / 541
页数:11
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