Performance Optimization and Evaluation of Space Management in Cloud Storage Systems

Abstract

Cloud service providers and enterprises usually deploy high performance storage to manage the unrelenting growth of data. In this paper, we focus on performance optimization and evaluation by using optimal regeneration codes in such cloud storage systems. We present an efficient data maintenance management framework to reduce network repair traffic with the minimum data movement while keeping the desired fault-tolerance in storage systems. In the management framework, it has two phases including the traditional erasure coding process and the optimal placement process. We formally represent the optimal placement as a variant of the bin packing problem by bipartite graphs. Then, we model the placement transform by the interchange graph and propose an efficient heuristic algorithm to find the optimal solution. All feasible solutions are linked together by interchange operation and thus the search space can be taken as an interchange graph. Finally, we evaluate the performance of the optimal placement during data maintenance with different practical settings in our experiments. The experimental results show that the amount of network repair traffic can be reduced by about $10\,\%$ than the initial placement and by about 2X than traditional erasure coding placement.