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

被引:0
|
作者
Cheng, Kang [1 ]
Teng, Yinglei [1 ]
Sun, Weiqi [1 ]
Liu, An [2 ]
Wang, Xianbin [3 ]
机构
[1] BUPT, Dept EE, Beijing Key Lab Spaceground Interconnect & Conver, Beijing, Peoples R China
[2] HKUST, Dept ECE, Hong Kong, Peoples R China
[3] Univ Western Ontario, Dept ECE, London, ON, Canada
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Mobile edge computing(MEC); task offloading scheduling; subcarrier allocation; bi-level optimization;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 multiuser 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.
引用
收藏
页数:6
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