Intelligent search in social communities of smartphone users

  • Authors:

  • Andreas Konstantinidis;Demetrios Zeinalipour-Yazti;Panayiotis Andreou;George Samaras;Panos K. Chrysanthis

  • Affiliations:

  • Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Department of Computer Science, University of Cyprus, Nicosia, Cyprus;Department of Computer Science, University of Pittsburgh, Pittsburgh, USA

  • Venue:
  • Distributed and Parallel Databases
  • Year:
  • 2013

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Abstract

Social communities of smartphone users have recently gained significant interest due to their wide social penetration. The applications in this domain, however, currently rely on centralized or cloud-like architectures for data sharing and searching tasks, introducing both data-disclosure and performance concerns. In this paper, we present a distributed search architecture for intelligent search of objects in a mobile social community. Our framework, coined SmartOpt, is founded on an in-situ data storage model, where captured objects remain local on smartphones and searches then take place over an intelligent multi-objective lookup structure we compute dynamically. Our MO-QRT structure optimizes several conflicting objectives, using a multi-objective evolutionary algorithm that calculates a diverse set of high quality non-dominated solutions in a single run. Then a decision-making subsystem is utilized to tune the retrieval preferences of the query user. We assess our ideas both using trace-driven experiments with mobility and social patterns derived by Microsoft's GeoLife project, DBLP and Pics `n' Trails but also using our real Android SmartP2P ( http://smartp2p.cs.ucy.ac.cy/ ) system deployed over our SmartLab ( http://smartlab.cs.ucy.ac.cy/ ) testbed of 40+ smartphones. Our study reveals that SmartOpt yields high query recall rates of 95 %, with one order of magnitude less time and two orders of magnitude less energy than its competitors.