Rank-energy selective query forwarding for distributed search systems

  • Authors:

  • Amin Teymorian;Ophir Frieder;Marcus A. Maloof

  • Affiliations:

  • Georgetown University, Washington, DC, USA;Georgetown University, Washington, DC, USA;Georgetown University, Washington, DC, USA

  • Venue:
  • Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
  • Year:
  • 2013

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Abstract

Scaling high-quality, cost-efficient query evaluation is critical to search system performance. Although partial indexes reduce query processing times, result quality may be jeopardized due to exclusion of relevant non-local documents. Selectively forwarding queries between geographically distributed search sites may help. The basic idea of query forwarding is that after a local site receives a query, it determines non-local sites to forward the query to and returns an aggregation of the local and non-local results. Nevertheless, electricity costs remain substantial sources of operating expenses. We present a hybrid rank-energy query forwarding model termed "RESQ." The novel contribution is to simultaneously consider both ranking quality and spatially-temporally varying energy prices when making forwarding decisions. Experiments with a large-scale query log, publicly-available electricity price data, and real search site locations demonstrate that query forwarding under RESQ achieves the result scalability of partial indexes with the cost savings of energy-aware approaches (e.g., an 87% ranking guarantee with a 46% savings in energy costs).