Fuzzy-Based Microservice Resource Management Platform for Edge Computing in the Internet of Things

Abstract

Edge computing exhibits the advantages of real-time operation, low latency, and low network cost. It has become a key technology for realizing smart Internet of Things applications. Microservices are being used by an increasing number of edge computing networks because of their sufficiently small code, reduced program complexity, and flexible deployment. However, edge computing has more limited resources than cloud computing, and thus edge computing networks have higher requirements for the overall resource scheduling of running microservices. Accordingly, the resource management of microservice applications in edge computing networks is a crucial issue. In this study, we developed and implemented a microservice resource management platform for edge computing networks. We designed a fuzzy-based microservice computing resource scaling (FMCRS) algorithm that can dynamically control the resource expansion scale of microservices. We proposed and implemented two microservice resource expansion methods based on the resource usage of edge network computing nodes. We conducted the experimental analysis in six scenarios and the experimental results proved that the designed microservice resource management platform can reduce the response time for microservice resource adjustments and dynamically expand microservices horizontally and vertically. Compared with other state-of-the-art microservice resource management methods, FMCRS can reduce sudden surges in overall network resource allocation, and thus, it is more suitable for the edge computing microservice management environment.

An Attention Mechanism-Based Microservice Placement Scheme for On-Star Edge Computing Nodes

“…Xu et al [25] proposed an enhanced service framework based on microservice management for efficient access to services in edge computing environments. Li et al [26] designed a fuzzy-based microservice computing resource scaling algorithm for a microservice management platform that can reduce the response time of microservice resource adjustment and achieve dynamic scaling of microservices both horizontally and vertically. Research on microservice management, as represented by Xu et al, has driven the development of edge computing, compared to researchers who have done relatively little research on the placement phase of microservices.…”