Instance optimal query processing in spatial networks

  • Authors:

  • Ke Deng;Xiaofang Zhou;Heng Tao Shen;Shazia Sadiq;Xue Li

  • Affiliations:

  • School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia 4072;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia 4072;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia 4072;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia 4072;School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia 4072

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2009

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Abstract

The performance optimization of query processing in spatial networks focuses on minimizing network data accesses and the cost of network distance calculations. This paper proposes algorithms for network k-NN queries, range queries, closest-pair queries and multi-source skyline queries based on a novel processing framework, namely, incremental lower bound constraint. By giving high processing priority to the query associated data points and utilizing the incremental nature of the lower bound, the performance of our algorithms is better optimized in contrast to the corresponding algorithms based on known framework incremental Euclidean restriction and incremental network expansion. More importantly, the proposed algorithms are proven to be instance optimal among classes of algorithms. Through experiments on real road network datasets, the superiority of the proposed algorithms is demonstrated.