A Novel Cost-aware Data Placement Strategy for Edge-Cloud Collaborative Smart Systems

Currently, smart systems are widely used in various scenarios such as smart cities, smart healthcare and smart logistics. Meanwhile, centralized cloud computing has become the mainstream platform for smart systems due to the strong demand for huge data storage and processing capacities. Edge computing can effectively reduce network latency and improve service response time for smart systems. However, edge servers are usually limited with data storage and processing capacities. Therefore, how to utilize both cloud and edge servers effectively is an open issue. In this paper, we focus on the problem of data placement in an edge-cloud collaborative smart system. Specifically, we propose a Differential Evolution Particle Swarm Optimization based data placement strategy (called DE-PSO) to optimize the data storage cost under deadline constraints. DE-PSO considers different features, requirements and environments of edge and cloud data storage services to generate an optimized data placement scheme. The comprehensive experimental results show that the proposed strategy proves its superior performance compared with several representative data placement strategies.