In order to ensure the load balance of network storage and to avoid unrecoverable loss in case of node or disk failures, this paper proposed a distributed storage and coding scheme based on balanced data placement strategy, which gave different solutions for large caches and small caches. Firstly, it extended the Maddah scheme to multi-server system, and stored each file as a unit in the data server by combining balanced data placement strategy to solve the large-scale cache problem. Then, it extended the interference cancellation scheme to the multi-server system. It used the interference cancellation scheme to reduce the peak rate of the cache, and proposed the linear combination of cache segments by combining balanced data placement strategy so as to solving the problem of small caching. Finally, it carried out simulation experiments in one and two parity check server systems respectively through Linux-based NS2 simulation software. The simulation results show that the proposed scheme can effectively reduce the peak transmission rate. It achieves better performance comparing with the other two new caching schemes. In addition, although distributed storage limits the ability to combine content from different servers into a single message, resulting in performance loss of coding and caching schemes, it can make full use of the inherent redundancy in distributed storage systems, thereby improving the performance of storage systems.

[2020-04-05] Printed Article /doc/2018.11.0836/v2