Cloud Storage Design Based on Hybrid of Replication and Data Partitioning

Most existing works on data partitioning techniques simply consider to partition data objects and distribute the shares to servers. Such pure data partitioning approaches may bring potential performance and scalability problems when used in widely distributed systems. First, it is difficult to apply lazy update. Second, the share consistency verification may incur costly communications among widely distributed servers. In this paper, we propose a two-level DHT (TDHT) approach for widely distributed cloud storage to address these problems. First, we analyze the tradeoffs on security and availability between TDHT and the conventional pure data partitioning approach (integrated with DHT and called GDHT (global DHT)). The results show that TDHT can provide better security than GDHT and almost the same level of availability as GDHT. To compare their performance, we design a two-level access (TLA) protocol for the TDHT approach and compare it with the distributed version server (DVS) protocol proposed in [Ye10] for the GDHT approach. The experimental results show that TLA can provide much better user perceived update response latency and the same level or even better read access latency compared to DVS.