A Lightweight Multidimensional Index for Complex Queries over DHTs

In this paper, we study the problem of indexing multidimensional data in P2P networks based on distributed hash tables (DHTs). We advocate the indexing approach that superimposes a multidimensional index tree on top of a DHT - a paradigm that keeps the underlying DHT intact while being able to adapt to any DHT substrate. In this context, we identify several index design issues and propose a novel indexing scheme called multidimensional Lightweight Hash Tree (m-LIGHT). First, to preserve data locality, m-LIGHT employs a clever naming mechanism that gracefully maps a tree-based index into the DHT and contributes to high efficiency in both index maintenance and query processing. Second, to tackle the load balancing issue, m-LIGHT leverages a new data-aware splitting strategy that achieves optimal load balance under a fixed index size. We present detailed algorithms for processing complex queries over the m-LIGHT index. We also conduct an extensive performance evaluation of m-LIGHT in comparison with several state-of-the-art indexing schemes. The experimental results show that m-LIGHT substantially reduces index maintenance overhead and improves query performance in terms of both bandwidth consumption and response latency.