Multi-objective optimization of container-based microservice scheduling in edge computing

Abstract

Edge computing provides physical resources closer to end users, becoming a good complement to cloud computing. With the rapid development of container technology and microservice architecture, container orchestration has become a hot issue. However, the container-based microservice scheduling problem in edge computing is still urgent to be solved. In this paper, we first formulate the container-based microservice scheduling as a multi-objective optimization problem, aiming to optimize network latency among microservices, reliability of microservice applications and load balancing of the cluster. We further propose a latency, reliability and load balancing aware scheduling (LRLBAS) algorithm to determine the container-based microservice deployment in edge computing. Our proposed algorithm is based on particle swarm optimization (PSO). In addition, we give a handling strategy to separate the fitness function from constraints, so that each particle has two fitness values. In the proposed algorithm, a new particle comparison criterion is introduced and a certain proportion of infeasible particles are reserved adaptively. Extensive simulation experiments are conducted to demonstrate the effectiveness and efficiency of the proposed algorithm compared with other related algorithms.