Frugal Sensor Assignment

  • Authors:
  • Matthew P. Johnson;Hosam Rowaihy;Diego Pizzocaro;Amotz Bar-Noy;Stuart Chalmers;Thomas Porta;Alun Preece

  • Affiliations:
  • Dept. of Computer Science, Graduate Center, City University of New York, USA;Dept. of Computer Science and Engineering, Pennsylvania State University, USA;School of Computer Science, Cardiff University, UK;Dept. of Computer Science, Graduate Center, City University of New York, USA;Department of Computing Science, University of Aberdeen, UK;Dept. of Computer Science and Engineering, Pennsylvania State University, USA;School of Computer Science, Cardiff University, UK

  • Venue:
  • DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
  • Year:
  • 2008

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Abstract

When a sensor network is deployed in the field it is typically required to support multiple simultaneous missions, which may start and finish at different times. Schemes that match sensor resources to mission demands thus become necessary. In this paper, we consider new sensor-assignment problems motivated by frugality, i.e., the conservation of resources, for both static and dynamic settings. In general, the problems we study are NP-hard even to approximate, and so we focus on heuristic algorithms that perform well in practice. In the static setting, we propose a greedy centralized solution and a more sophisticated solution that uses the Generalized Assignment Problem model and can be implemented in a distributed fashion. In the dynamic setting, we give heuristic algorithms in which available sensors propose to nearby missions as they arrive. We find that the overall performance can be significantly improved if available sensors sometimes refuse to offer utility to missions they could help based on the value of the mission, the sensor's remaining energy, and (if known) the remaining target lifetime of the network. Finally, we evaluate our solutions through simulations.