Service cost-based resource optimization and load balancing for edge and cloud environment

Abstract

The application of edge clouds is becoming more and more widespread. The resource optimization is one of the important research contents of edge cloud. Generally, the edge cloud has limited computing resources and energy. Resource optimization can make tasks perform efficiently and reduce costs. Therefore, achieving high energy efficiency while ensuring a satisfying user experience is critical. This paper proposes the resource optimization and load balancing model. By considering factors such as user preferences, SLA and cost, the algorithm of resource optimization determines the resources scheme of edge cloud. The data movement after resource optimization is achieved through migration strategies. The load balancing of the edge cloud environment can be ensured. The results of the experiment prove that our proposed algorithm can better control costs.