Efficient R-Tree Based Indexing for Cloud Storage System with Dual-Port Servers

Cloud storage system such as Amazon’s Dynamo and Google’s GFS poses new challenges to the community to support efficient query processing for various applications. In this paper we propose RT-HCN, a distributed indexing scheme for multi-dimensional query processing in data centers, the infrastructure to build cloud systems. RT-HCN is a two-layer indexing scheme, which integrates HCN-based routing protocol and the R-Tree based indexing technology, and is portionably distributed on every server. Based on the characteristics of HCN, we design a special index publishing rule and query processing algorithms to guarantee efficient data management for the whole network. We prove theoretically that RT-HCN is both query-efficient and space-efficient, by which each server will only maintain a tolerable number of indices while a large number of users can concurrently process queries with low routing cost. We compare our design with RT-CAN, a similar design in traditional P2P network. Experiments validate the efficiency of our proposed scheme and depict its potential implementation in data centers.