A Minimal-overhead Multi-cloud Data Placement Strategy Based on Heuristic Algorithm

Abstract

Multi-cloud storage can provide better service levels than single cloud storage in terms of confidentiality, integrity, and availability at a low cost. More and more customers are storing data in multi-cloud storage systems. However, inefficient data placement is a challenge for multi-cloud storage, and current research has the problem of low algorithm efficiency. In response to this problem, a multi-cloud storage data placement optimization strategy, MPO-MO, is proposed for minimum overhead requirements. MPO-MO models availability and cost, and provides users with the lowest cost multi-cloud storage data placement strategy while meeting the specified availability constraints. A heuristic algorithm is proposed, which uses the sorting information of storage price and traffic price to select cloud storage services. According to analysis, the heuristic algorithm adopted by MPO-MO greatly reduces the optimization space compared with the traditional algorithm, and the efficiency is significantly improved. Finally, experiments prove the effectiveness of MPO-MO.