An efficient peer-to-peer indexing tree structure for multidimensional data

As one of the most important technology for implementing large-scale distributed systems, peer-to-peer (P2P) computing has attracted much attention in both research and academia communities, for its advantages such as high availability, high performance, and high flexibility to the dynamics of networks. However, multidimensional data indexing remains as a big challenge to P2P computing, because of the inefficiency in search and network maintenance caused by the complicated existing index structures, which greatly limits the scalability of applications and dimensionality of data to be indexed. We propose SDI (Swift tree structure for multidimensional Data Indexing), a swift index scheme with simple tree structure for multidimensional data indexing in large-scale distributed systems. While keeping the query efficiency in O(log N) in terms of routing hops, SDI has extremely low maintenance cost which is proved through theoretical analysis. Furthermore, SDI overcomes the root-bottleneck problem existing in most other tree-based distributed indexing techniques. Extensive empirical study verify the superiority of SDI in both query and maintenance performance.