Sensor Network Coverage Problem: A Hypergraph Model Approach

  • Krzysztof Trojanowski
  • Artur Mikitiuk
  • Mateusz Kowalczyk
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)


A sensor power schedule for a homogenous network of sensors with a limited battery capacity monitoring a set of points of interest (POI) depends on locations of POIs and sensors, monitoring range and battery lifetimes. A good schedule keeps the network operational as long as possible while maintaining the required level of coverage (not all POIs have to be monitored all the time). Searching for such a schedule is known as the Maximum Lifetime Coverage Problem. A new approach solving MLCP is proposed in this paper. First, in every time step, we try to achieve the required coverage level using sensors with the longest remaining working time monitoring the largest number of POIs that have not been covered yet. The resulting schedule is next used for generating a neighbour schedule by a perturbation algorithm. For experimental evaluation of our approach a new set of test cases is proposed. Experiments with these data show interesting properties of the algorithm.


  1. 1.
    Cardei, I., Cardei, M.: Energy-efficient connected-coverage in wireless sensor networks. IJSNet 3(3), 201–210 (2008)CrossRefGoogle Scholar
  2. 2.
    Halton, J.H.: Algorithm 247: radical-inverse quasi-random point sequence. Commun. ACM 7(12), 701–702 (1964)CrossRefGoogle Scholar
  3. 3.
    Tian, D., Georganas, N.D.: A coverage-preserving node scheduling scheme for large wireless sensor networks. In: Proceeding of the First ACM Int. Workshop on Wireless Sensor Networks and Applications (WSNA-2002), pp. 32–41. ACM Press (2002)Google Scholar
  4. 4.
    Tretyakova, A., Seredynski, F.: Application of evolutionary algorithms to maximum lifetime coverage problem in wireless sensor networks. In: IPDPS Workshops, pp. 445–453. IEEE (2013)Google Scholar
  5. 5.
    Tretyakova, A., Seredynski, F.: Simulated annealing application to maximum lifetime coverage problem in wireless sensor networks. In: Global Conference on Artificial Intelligence, GCAI, vol. 36, pp. 296–311. EasyChair (2015)Google Scholar
  6. 6.
    Tretyakova, A., Seredynski, F., Bouvry, P.: Graph cellular automata approach to the maximum lifetime coverage problem in wireless sensor networks. Simulation 92(2), 153–164 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Krzysztof Trojanowski
    • 1
  • Artur Mikitiuk
    • 1
  • Mateusz Kowalczyk
    • 1
  1. 1.Cardinal Stefan Wyszyński University in WarsawWarszawaPoland

Personalised recommendations