Implementing Range Queries with a Decentralized Balanced Tree over Distributed Hash Tables

Abstract

Range queries, retrieving all keys within a given range, is an important add-on for Distributed Hash Tables (DHTs), as they rely only on exact key matching lookup. In this paper we support range queries through a balanced tree algorithm, Decentralized Balanced Tree, that runs over any DHT system. Our algorithm is based on the B+-tree design that efficiently stores clustered data while maintaining a balanced load on hosts. The internal structure of the balanced tree is suited for range queries operations over many data distributions since it easily handles clustered data without losing performance. We analyzed, and evaluated our algorithm under a simulated environment, to show it's operation scalability for both insertions and queries. We will show that the system design imposes a fixed penalty over the DHT access cost, and thus inherits the scalability properties of the chosen underlying DHT.