Evaluating graph traversal algorithms for distributed SPARQL query optimization

Distributed SPARQL queries enable users to retrieve information by exploiting the increasing amount of linked data being published. However, industrial-strength distributed SPARQL query processing is still at its early stage for efficiently answering queries. Previous research shows that it is possible to apply methods from graph theory to optimize the performance of distributed SPARQL. In this paper we describe a framework that can simulate arbitrary RDF data networks to evaluate different approaches of distributed SPARQL query processing. Using this framework we further explore the graph traversal algorithms for distributed SPARQL optimization. We present an implementation of a Minimum-Spanning-Tree-based (MST-based) algorithm for distributed SPARQL processing, the performance of which is compared to other approaches using this evaluation framework. The contribution of this paper is to show that a MST-based approach seems to perform much better than other non graph-traversal-based approaches, and to provide an evaluation framework for evaluating distributed SPARQL processing