DHT-Based Range Query Processing for Web Service Discovery

DHTs are scalable, self-organizing, and adaptive to underlying topology changes, thus being a promising infrastructure for realizing efficient Web service discovery. Range queries play an important role in service discovery, and in recent years a number of DHT-based range query schemes have been proposed. However, most of them suffer from high query delay and high processing cost. This paper presents ERQ, an Efficient scheme for delay bounded Range Query processing over DHTs. We first emulate the PHT structure and design a balanced Kautz (BK) tree to uniformly map the m-dimensional data space onto DHT nodes, and then present a novel algorithm that processes range queries in a parallel fashion, where an on-the-fly space pruning mechanism is adopted to reduce the processing cost. In a DHT with N nodes, ERQ can answer any range query in less than logN (2loglogN+1) hops with low processing cost, irrespective of the queried range, the whole space size, or the number of queried attributes. The effectiveness of ERQ is demonstrated through extensive experiments.