一种云存储环境下的资源调度改进算法

How to store the user's massive data into the data center with the minimum time-consuming is the key issue to be considered in improving cloud storage efficiency and solving the bottleneck of its development. This paper first proved that the minimum storage time-consuming of resource scheduling scheme in cloud storage environment belongs to NPC problem. In view of the incomplete consideration of the existing scheduling algorithms and the problem that the scheduling result tends to fall into the local optimum, a new resource scheduling algorithm was proposed. The algorithm firstly used the triangular fuzzy analytic hierarchy process method to comprehensively analyze the scheduling effecting factors, the judgment matrix of storage nodes was obtained, which was used to construct the follow-up objective function of genetic algorithm, and then the simple genetic algorithm was innovated from the perspective of encoding, cross-mutation operation and self-improvement of lethal chromosome so that it is suitable for cloud storage environment. Finally, this paper analyzed and compared the Cinder block storage algorithm in OpenStack and the existing improved algorithms. The experimental results verified the effectiveness of the proposed algorithm and achieved more efficient resource scheduling.