Open Access

ARTICLE

Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

by Jixun Gao^1,2, Bingyi Hu², Jialei Liu^3,4,*, Huaichen Wang⁵, Quanzhen Huang¹, Yuanyuan Zhao⁶

1 School of Computer, Henan University of Engineering, Zhengzhou, 451191, China
2 School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, China
3 School of Computer, Hubei University of Arts and Science, Xiangyang, 441053, China
4 School of Software Engineering, Anyang Normal University, Anyang, 455000, China
5 School of Computer and Information Engineering, Henan Normal University, Xinxiang, 453003, China
6 The Publicity Department, Zhengzhou University of Technology, Zhengzhou, 450044, China

* Corresponding Author: Jialei Liu. Email:

Intelligent Automation & Soft Computing 2023, 37(1), 1-16. https://doi.org/10.32604/iasc.2023.036890

Received 15 October 2022; Accepted 23 November 2022; Issue published 29 April 2023

Abstract

Mobile Edge Computing (MEC) is proposed to solve the needs of Internet of Things (IoT) users for high resource utilization, high reliability and low latency of service requests. However, the backup virtual machine is idle when its primary virtual machine is running normally, which will waste resources. Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization. First, these virtual machines are deployed into slots randomly, and then some tasks with cooperative relationship are offloaded to virtual machines for processing. Different deployment locations have different resource utilization and average service response time. We want to find a balanced solution that minimizes the average service response time of the IoT application while maximizing resource utilization. In this paper, we propose a task scheduler and exploit a Task Deployment Algorithm (TDA) to obtain an optimal virtual machine deployment scheme. Finally, the simulation results show that the TDA can significantly increase the resource utilization of the system, while reducing the average service response time of the application by comparing TDA with the other two classical methods. The experimental results confirm that the performance of TDA is better than that of other two methods.

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Keywords

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