Research on Mobile Edge Computing Resource Allocation with Energy Harvesting Device

doi:10.16182/j.issn1004731x.joss.21-0576

Abstract

Abstract:

In order to solve the problem of computing resource allocation of mobile edge computing system with energy gathering ability, an algorithm based on Lyapunov greed optimization (LGO) is proposed. This paper presents a dynamic optimization problem to minimize the combined cost of time delay and energy consumption of mobile devices under the gradual convergence of equipment battery power. Using Lyapunov dynamic optimization theory, the optimization problem is decomposed into three sub-problems of optimal local execution, unloading execution and energy harvesting for each time slot, and the optimal solution of the sub-problems is obtained by linear programming. By selecting the execution mode between local execution, unload execution and task discarding, the combined cost of time delay and energy consumption of the vehicle can be minimized. The greedy policy program is designed by using key-value pairs to adapt to multi-user and multi-server systems. The simulation results show that under the condition that the battery power of all equipment is stable around the specified operating level, the unloading rate can reach more than 99.9%, and the service delay and system energy consumption can be effectively reduced.

Key words: energy harvesting, Lyapunov optimization, edge computing, computation offloading, resource allocation

CLC Number:

TP301
TP391

Changyun Li, Jianbo Li, Xi Xu, Tingli Li. Research on Mobile Edge Computing Resource Allocation with Energy Harvesting Device[J]. Journal of System Simulation, 2022, 34(11): 2313-2322.

Figures/Tables 9

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参数名称	参数符号	参数取值
移动设备数量(个)	N	10
MEC服务器数量(个)	M	5
信道宽度/Hz	ω	1e6
完成任务所需周期数(个)	W	737 500
时隙长度/s	τ	2e-3
任务大小/bit	L	1 000
执行截止时间/s	tau_d	2e-3
设备CPU计算能力	X	737.5
有效开关电容	δ	1e-28
任务删除成本/J	phi	2e-3
接收机的噪声功率/W	σ	1e-13
设备最大发射功率/W		1
设备最大CPU频率/Hz	f_max	1.5e9
采集能量上限/J		48e-6
电池最小输出能量/J	E_min	2e-5
惩罚权	V	1e-5
MEC服务器最大连接数量(个)	S	4