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

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 and Technology, 7(4.29), 228-231. https://doi.org/10.14419/ijet.v7i4.29.26260

Received date: January 20, 2019

Accepted date: January 20, 2019

Published date: November 26, 2018

DOI:

https://doi.org/10.14419/ijet.v7i4.29.26260

Keywords:

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.

 


 

References

  1. Ai, J. and Abouzeid, A. A. (2006). Coverage by directional sensors in randomly deployed wireless sensor networks. Journal of Combinatorial Optimization, 11(1):21–41.

    [2] Cai, Y., Lou, W., Li, M., and Li, X.-Y. (2009). Energy efficient target-oriented scheduling in directional sensor networks. IEEE Transactions on Computers, 58(9):1259–1274.

    [3] Gil, J.-M. and Han, Y.-H. (2011). A target coverage scheduling scheme based on genetic algorithms in directional sensor networks. Sensors, 11(2):1888–1906.

    [4] Guvensan, M. A. and Yavuz, A. G. (2011). On coverage is- sues in directional sensor networks: A survey. Ad Hoc Networks, 9(7):1238–1255.

    [5] Mohamadi, H., Ismail, A. S., and Salleh, S. (2013a). Utilizing distributed learning automata to solve the connected target coverage problem in directional sensor networks. Sensors and Actuators A: Physical, 198:21–30.

    [6] Mohamadi, H., Ismail, A. S., and Salleh, S. (2014a). Solving tar- get coverage problem using cover sets in wireless sensor networks based on learning automata. Wireless personal communications, 75(1):447–463.

    [7] Mohamadi, H., Ismail, A. S., Salleh, S., and Nodhei, A. (2013b). Learning automata-based algorithms for finding cover sets in wire- less sensor networks. The Journal of Supercomputing, 66(3):1533–1552.

    [8] Mohamadi, H., Ismail, A. S. B. H., and Salleh, S. (2013c). A learning automata-based algorithm for solving coverage problem in directional sensor networks. Computing, 95(1):1–24.

    [9] Mohamadi, H., Salleh, S., and Ismail, A. S. (2014b). A learning automata-based solution to the priority-based target coverage problem in directional sensor networks. Wireless Personal Communications, 79(3):2323–2338.

    [10] Mohamadi, H., Salleh, S., and Razali, M. N. (2014c). Heuristic methods to maximize network lifetime in directional sensor networks with adjustable sensing ranges. Journal of Network and Computer Applications, 46:26–35.

    [11] Najim, K. and Poznyak, A. S. (2014). Learning automata: theory and applications. Elsevier.

    [12] Razali, M. N., Salleh, S., & Mohamadi, H. (2017). Solving priority-based target coverage problem in directional sensor networks with adjustable sensing ranges. Wireless Personal Communications, 95(2), 847-872.

    [13] Wang, J., Niu, C., and Shen, R. (2009). Priority-based target coverage in directional sensor networks using a genetic algorithm. Computers & Mathematics with Applications, 57(11):1915–1922.

    [14] Yang, H., Li, D., and Chen, H. (2010). Coverage quality-based target-oriented scheduling in directional sensor networks. In Communications (ICC), 2010 IEEE International Conference on, pages 1–5. IEEE.

    [15] Yick, J., Mukherjee, B., and Ghosal, D. (2008). Wireless sensor network survey. Computer networks, 52(12):2292–2330.

    [16] Zorbas, D. and Douligeris, C. (2011). Connected coverage in WSNs based on critical targets. Computer Networks, 55(6):1412–1425.

    [17] Zorbas, D. and Razafindralambo, T. (2013). Prolonging network lifetime under probabilistic target coverage in wireless mobile sensor networks. Computer Communications, 36(9):1039–1053.

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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 and Technology, 7(4.29), 228-231. https://doi.org/10.14419/ijet.v7i4.29.26260

Received date: January 20, 2019

Accepted date: January 20, 2019

Published date: November 26, 2018