RFH: A Resilient, Fault-Tolerant and High-Efficient Replication Algorithm for Distributed Cloud Storage

To avoid failure and achieve higher availability, replication scheme is now widely used in distributed Cloud storage systems [25]. However, most of them only statically replicate data on some randomly chosen nodes for a fixed number of times and it is obviously not enough for more reasonable resource allocation. Moreover, query load for Web application is highly irregular. It throws us into a dilemma to always maintain maximum number of replicas in case of explosive query load outburst or save resources with fewer replicas at the expense of performance. In this paper, we present a Resilient, Fault-tolerant and High-efficient global replication algorithm (RFH) for distributed Cloud storage systems. RFHis especially efficient facing ´flash crowd´ problem. Each data partition is represented by a virtual node. Each virtual node itself decides whether to replicate, migrate or suicide by weighing up the pros and cons. It is based on the evaluation of traffic load of all nodes, and selects among physical nodes with the most traffic (traffic hub) to replicate or migrate on. After that, it takes into account blocking probability to achieve quicker response and better load balance performance. Extensive simulations have been conducted and the results have demonstrated that the proposed scheme RFH outperforms the main existing algorithms the request-oriented algorithms[16] [5], the owner-oriented algorithms [7] [11] [12] [13] and the random algorithms [4] [21] [22] in terms of high replica utilization rate, high query efficiency and reasonable path length at a low cost while maintaining high availability.