An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers

Yanjun Shi, Yijia Guo, Lingling Lv and Keshuai Zhang
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Yanjun Shi: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Yijia Guo: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Lingling Lv: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
Keshuai Zhang: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China

Future Internet, 2020, vol. 12, issue 10, 1-15

Abstract: The fast development of connected vehicles with support for various V2X (vehicle-to-everything) applications carries high demand for quality of edge services, which concerns microservice deployment and edge computing. We herein propose an efficient resource scheduling strategy to containerize microservice deployment for better performance. Firstly, we quantify three crucial factors (resource utilization, resource utilization balancing, and microservice dependencies) in resource scheduling. Then, we propose a multi-objective model to achieve equilibrium in these factors and a multiple fitness genetic algorithm (MFGA) for the balance between resource utilization, resource utilization balancing, and calling distance, where a container dynamic migration strategy in the crossover and mutation process of the algorithm is provided. The simulated results from Container-CloudSim showed the effectiveness of our MFGA.

Keywords: containerized microservice; resource scheduling; edge computing (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
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