Abstract
We study the problem of distributed RDFS reasoning and query answering on top of distributed hash tables. Scalable, distributed RDFS reasoning is an essential functionality for providing the scalability and performance that large-scale Semantic Web applications require. Our goal in this paper is to compare and evaluate two well-known approaches to RDFS reasoning, namely backward and forward chaining, on top of distributed hash tables. We show how to implement both algorithms on top of the distributed hash table Bamboo and prove their correctness. We also study the time-space trade-off exhibited by the algorithms analytically, and experimentally by evaluating our algorithms on PlanetLab. © 2008 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Kaoudi, Z., Miliaraki, I., & Koubarakis, M. (2008). RDFS reasoning and query answering on top of DHTs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5318 LNCS, pp. 499–516). Springer Verlag. https://doi.org/10.1007/978-3-540-88564-1_32
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