Resource and replica management strategy for optimizing financial cost and user experience in edge cloud computing system

Abstract

Edge cloud computing can provide resources that are close to users and reduce response time. However, the edge cloud computing system still faces many challenges on addressing the overload problem due to its limited capacity. In this paper, a resource management strategy is proposed to satisfy the workloads of the edge cloud, while minimizing the financial cost of the rented nodes. Furthermore, the replica management strategy, which consists of the replica allocation and consistency preservation strategy, is studied. A dynamic replica allocation strategy is proposed to satisfy the user experience while reducing the storage overheads. In addition, the replica consistency preservation strategy is proposed for guaranteeing the data consistency and correctness. Finally, extensive experiments are conducted based on a real-world dataset. With the increase in the time, the proposed resource management algorithm can significantly reduce the total financial cost of the rented nodes and SLA default rate and improve the CPU utilization. For instance, the total financial cost of the proposed algorithm averagely achieves up to 32.27% and 53.65% reduction over that of CAAS algorithm and DRM algorithm, respectively. In addition, the proposed replica allocation algorithm can effectively reduce the data transmission time and the storage overhead.