Sensor networks and distributed CSP: communication, computation and complexity

  • Authors:

  • Ramón Béjar;Carmel Domshlak;Cèsar Fernández;Carla Gomes;Bhaskar Krishnamachari;Bart Selman;Magda Valls

  • Affiliations:

  • Departament d'Informàtica i Enginyeria Industrial, Universitat de Lleida, Lleida, Spain;Department of Computer Science, Cornell University, Ithaca, NY;Departament d'Informàtica i Enginyeria Industrial, Universitat de Lleida, Lleida, Spain;Department of Computer Science, Cornell University, Ithaca, NY;Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA;Department of Computer Science, Cornell University, Ithaca, NY;Departament de Matemàtica, Universitat de Lleida, Lleida, Spain

  • Venue:
  • Artificial Intelligence - Special issue: Distributed constraint satisfaction
  • Year:
  • 2005

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Abstract

We introduce SensorDCSP, a naturally distributed benchmark based on a real-world application that arises in the context of networked distributed systems. In order to study the performance of Distributed CSP (DisCSP) algorithms in a truly distributed setting, we use a discrete-event network simulator, which allows us to model the impact of different network traffic conditions on the performance of the algorithms. We consider two complete DisCSP algorithms: asynchronous backtracking (ABT) and asynchronous weak commitment search (AWC), and perform performance comparison for these algorithms on both satisfiable and unsatisfiable instances of SensorDCSP. We found that random delays (due to network traffic or in some cases actively introduced by the agents) combined with a dynamic decentralized restart strategy can improve the performance of DisCSP algorithms. In addition, we introduce GSensorDCSP a plain-embedded version of SensorDCSP that is closely related to various real-life dynamic tracking systems. We perform both analytical and empirical study of this benchmark domain. In particular, this benchmark allows us to study the attractiveness of solution repairing for solving a sequence of DisCSPs that represent the dynamic tracking of a set of moving objects.