Overcoming limitations of term-based partitioning for distributed RDFS reasoning

  • Authors:

  • Tugba Kulahcioglu;Hasan Bulut

  • Affiliations:

  • Ege University, Bornova, Izmir, Turkey;Ege University, Bornova, Izmir, Turkey

  • Venue:
  • Proceedings of the Fifth Workshop on Semantic Web Information Management
  • Year:
  • 2013

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Abstract

RDFS reasoning is carried out via joint terms of triples; accordingly, a distributed reasoning approach should bring together triples that have terms in common. To achieve this, term-based partitioning distributes triples to partitions based on the terms they include. However, skewed distribution of Semantic Web data results in unbalanced load distribution. A single peer should be able to handle even the largest partition, and this requirement limits scalability. This approach also suffers from data replication since a triple is sent to multiple partitions. In this paper, we propose a two-step method to overcome above limitations. Our RDFS specific term-based partitioning algorithm applies a selective distribution policy and distributes triples with minimum replication. Our schema-sensitive processing approach eliminates non-productive partitions, and enables processing of a partition regardless of its size. Resulting partitions reach full closure without repeating the global schema or without fix-point iteration as suggested by previous studies.