Two-level indexing for high-dimensional range queries in peer-to-peer networks
Supporting complex and efficient lookup queries in peer-to-peer networks is challenging, though simple keyword based lookup queries are well supported by most deployed systems. This paper presents a two-level indexing structure built on Distributed Hash Table (DHT) aiming to support range queries on high-dimensional feature space in peer-to-peer network. Unlike most existing systems, where every node is responsible for a data partition, our design only utilizes a small part of the nodes to manage partitions. These partition nodes form the first level index. The second level index consists of one or more server nodes, which maintains links to each partition node. Additionally, a merge and split mechanism is designed to dynamically adjust the workload among nodes. Experimental results indicate that our system offers promising performance in terms of workload balance in churn networks. The flexibility to work with any DHT and the capability to support multiple feature spaces further make our proposed approach a feasible extension for file sharing networks.