Efficient top-k processing in large-scaled distributed environments

  • Authors:
  • Keping Zhao;Yufei Tao;Shuigeng Zhou

  • Affiliations:
  • Microsoft China, 3 Hong Qiao Road, Shanghai 200030, China;Department of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong;Department of Computer Science and Engineering, Fudan University, 220 Handan Road, Shanghai 200433, China

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2007

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Abstract

The rapid development of networking technologies has made it possible to construct a distributed database that involves a huge number of sites. Query processing in such a large-scaled system poses serious challenges beyond the scope of traditional distributed algorithms. In this paper, we propose a new algorithm BRANCA for performing top-k retrieval in these environments. Integrating two orthogonal methodologies ''semantic caching'' and ''routing indexes'', BRANCA is able to solve a query by accessing only a small number of servers. Our algorithmic findings are accompanied with a solid theoretical analysis, which rigorously proves the effectiveness of BRANCA. Extensive experiments verify that our technique outperforms the existing methods significantly.