An energy-efficient self-deployment with the centroid-directed virtual force in mobile sensor networks

  • Authors:
  • Youn-Hee Han;Yong-Hwan Kim;Wontae Kim;Young-Sik Jeong

  • Affiliations:
  • Laboratory of Intelligent Networks, Advanced Technology Research Center, Korea University of Technology and Education, South Korea;CPS Research Team, Embedded Software Research Department, Electronics and Telecommunications Research Institute (ETRI), South Korea;CPS Research Team, Embedded Software Research Department, Electronics and Telecommunications Research Institute (ETRI), South Korea;Grid Computing Laboratory, Wonkwang University, South Korea

  • Venue:
  • Simulation
  • Year:
  • 2012

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Abstract

The deployment of sensors at their intended locations enables not only adequate sensing coverage of the area of interest, but also efficient sensor resource management. However, for static wireless sensor networks, it is sometimes impossible to manually deploy the sensors in those locations as they can be distributed in unexploited, hostile, or disaster areas. Nevertheless, if each sensor has locomotive capability, they can re-deploy themselves using the location information of neighboring sensors. In particular, in our previous study, we showed that the coverage area can be efficiently expanded by having sensors move to the centroids of their Voronoi polygon generated using the location information of neighboring sensors. In this paper, we present an energy-efficient self-deployment scheme to utilize the attractive force generated from the centroid of a sensor's local Voronoi polygon as well as the repulsive force frequently used in self-deployment schemes using the potential field. We also provide the design and implementation of the simulator used to analyze the performance of the proposed approach as compared with existing self-deployment schemes. The simulation results show that our scheme can achieve a higher coverage and enables less sensor movements in shorter times than self-deployment schemes using the traditional potential field.