Learning Automata-Based Algorithm as a Solution to the Problem of Priority-Based Target Coverage in Directional Sensor Networks with Adjustable Sensing Ranges

  • Authors

    • Mohd Norsyarizad Razali
    • Shaharuddin Salleh
    • Mohd Azzeri Md Naiem
    2018-11-26
    https://doi.org/10.14419/ijet.v7i4.29.26260
  • cover set formation, directional sensor networks, learning automata, scheduling algorithms, target coverage problem.

  • Abstract

    The limited battery power and sensing angle of directional sensors makes maximizing the network lifetime of directional sensor networks (DSNs) a challenging problem, especially when surveillance of a set of targets in a given area is involved. Sensors with multiple ranges and targets that require varied coverage further exacerbate this problem. This study refers to this problem as PTCASR—Priority-based Target Coverage with Adjustable Sensing Ranges. A promising solution to this problem is to use a scheduling technique, which involves allocation of sensors into cover sets and their successive activation thereafter. A scheduling algorithm based on learning automata is proposed in this study as a solution to this problem. To assess the performance of the proposed algorithm in extending network lifetime, several simulations were conducted.

     


     

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  • How to Cite

    Norsyarizad Razali, M., Salleh, S., & Azzeri Md Naiem, M. (2018). Learning Automata-Based Algorithm as a Solution to the Problem of Priority-Based Target Coverage in Directional Sensor Networks with Adjustable Sensing Ranges. International Journal of Engineering & Technology, 7(4.29), 228-231. https://doi.org/10.14419/ijet.v7i4.29.26260

    Received date: 2019-01-20

    Accepted date: 2019-01-20

    Published date: 2018-11-26