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Pro-active Strategies for the Frugal Feeding Problem in Wireless Sensor Networks

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Abstract

This paper proposes a pro-active solution to the Frugal Feeding Problem (FFP) in Wireless Sensor Networks. The FFP attempts to find energy-efficient routes for a mobile service entity to rendezvous with each member of a team of mobile robots. Although the complexity of the FFP is similar to the Traveling Salesman Problem (TSP), we propose an efficient solution, completely distributed and localized for the case of a fixed rendezvous location (i.e., service facility with limited number of docking ports) and mobile capable entities (sensors). Our pro-active solution reduces the FFP to finding energy-efficient routes in a dynamic Compass Directed unit Graph (CDG). The proposed CDG incorporates ideas from forward progress routing and the directionality of compass routing in an energy-aware unit sub-graph. Navigating the CDG guarantees that each sensor will reach the rendezvous location in a finite number of steps. The ultimate goal of our solution is to achieve energy equilibrium (i.e., no further sensor losses due to energy starvation) by optimizing the use of the shared resource (recharge station). We also examine the impact of critical parameters such as transmission range, cost of mobility and sensor knowledge in the overall performance.

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© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Velazquez, E., Santoro, N., Lanthier, M. (2011). Pro-active Strategies for the Frugal Feeding Problem in Wireless Sensor Networks. In: Par, G., Morrow, P. (eds) Sensor Systems and Software. S-CUBE 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23583-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-23583-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23582-5

  • Online ISBN: 978-3-642-23583-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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