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access icon free Target coverage heuristic based on learning automata in wireless sensor networks

© The Institution of Engineering and Technology
Received 28/07/2017, Accepted 04/01/2018, Revised 20/11/2017, Published 08/01/2018

In wireless sensors networks, the sensor nodes are densely deployed. Owing to this excessive deployment of sensor nodes, each target is covered by multiple sensors at a time. To prolong the network lifetime, the authors can schedule the sensor activity in such a way that only a subset of sensor nodes, called cover set, is sufficient enough to cover all the targets. In this study, they propose an energy-efficient scheduling algorithm based on learning automata for target coverage problem. The learning automata-based technique helps a sensor node to select its appropriate state (either active or sleep). To prove the effectiveness of their proposed scheduling method, they conduct a detailed set of simulations and compare the performance of their algorithm with the existing algorithms.

Inspec keywords: learning automata; wireless sensor networks; telecommunication scheduling

Other keywords: learning automata-based technique; scheduling method; sensor nodes; learning automata; WSN; wireless sensor networks; target coverage heuristic; energy-efficient scheduling algorithm

Subjects: Wireless sensor networks

References

    1. 1)
      • 9. Manju, ., Pujari, A.K.: ‘High-energy-first (HEF) heuristic for energy efficient target coverage problem’, Int. J. Ad hoc Sens. Ubiquitous Comput., 2011, 2, (1), pp. 45–58.
    2. 2)
      • 5. Mostafaei, H., Montierib, A., Persicoc, V., et al: ‘A sleep scheduling approach based on learning automata for WSN partial coverage’, J. Netw. Comput. Appl., 2017, 80, pp. 67–78.
    3. 3)
      • 2. Esnaashari, M., Meybodi, M.R.: ‘Learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks’, Comput. Netw., 2010, 54, (14), pp. 2410–2438.
    4. 4)
      • 16. Mini, S., Udgata, S.K, Sabat, S.L.: ‘Sensor deployment and scheduling for target coverage problem in wireless sensor networks’, IEEE Sens. J., 2014, 14, (3), pp. 636–644.
    5. 5)
      • 21. Narendra, K.S., Thathachar, M.A.L.: ‘Learning automata: an introduction’ (Prentice-Hall, Englewood Cliffs, 1989).
    6. 6)
      • 17. Chaudhary, M., Pujari, A.K.: ‘Q-coverage problem in wireless sensor networks’. Int. Conf. Distrib. Comput. Netw., 2009, pp. 325–330.
    7. 7)
      • 15. Singh, S., Chand, S., Kumar, B.: ‘Heterogeneous HEED protocol for wireless sensor networks’, in ‘Wireless personal communications’ (Springer Science and Business Media, 2014), 77, (3), pp. 2117–2139.
    8. 8)
      • 23. Mohamadi, H., Ismail, A., Salleh, S., et al: ‘Learning automata-based algorithms for finding cover sets in wireless sensor networks’, J. Supercomput. (in press), 2013, 66, (3), pp. 1533–1552.
    9. 9)
      • 1. Jin, R., Che, Z., Wang, Z., et al: ‘Battery optimal scheduling based on energy balance in wireless sensor networks’, IET Wirel. Sens. Syst., 2015, 5, (6), pp. 277–282.
    10. 10)
      • 18. Salleh, S., Marouf, S., Mohammadi, H.: ‘A new learning automata-based algorithm to the priority-based target coverage problem in directional sensor networks’, in (Eds.): ‘Lecture notes of the institute for computer sciences, social-informatics and telecommunications engineering’, 2015, 141, pp. 219–229.
    11. 11)
      • 6. Mostafaei, H., Montieri, A., Persico, V., et al: ‘An efficient partial coverage algorithm for wireless sensor networks’. IEEE Symp. Computers and Communication (ISCC), Italy, 2016, pp. 1–6.
    12. 12)
      • 3. Mostafaei, H., Meybodi, M.R.: ‘Maximizing lifetime of target coverage in wireless sensor networks using learning automata’, Wirel. Pers. Commun., 2013, 71, (2), pp. 1461–1477.
    13. 13)
      • 14. Mostafaei, H., Meybodi, M., Esnaashari, M.: ‘EEMLA: energy efficient monitoring of wireless sensor network with learning automata’. Int. Conf. Signal Acquisition and Processing, 2010, pp. 107–111.
    14. 14)
      • 20. Mohamadi, H., Salleh, S., Razali, M.N., et al: ‘A new learning automata-based approach for maximizing network lifetime in wireless sensor networks with adjustable sensing ranges’, Neurocomputing, 2015, 153, pp. 11–19.
    15. 15)
      • 10. Salleh, S., Marouf, S: ‘A learning automata-based solution to the target coverage problem in wireless sensor networks’. ACM Int. Conf. Proceeding Series, 2013, pp. 185–190.
    16. 16)
      • 8. Mohamadi, H., Ismail, A.S., Salleh, S.: ‘Solving target coverage problem using cover sets in wireless sensor networks based on learning automata’, Wirel. Pers. Commun., 2014, 75, pp. 447–463.
    17. 17)
      • 12. Pujari, A.K, Mini, S., Padhi, T., et al: ‘Polyhedral approach for lifetime maximization of target coverage problem’. Int. Conf. Distrib. Comput. Netw., 2015, 14, 1, 14:8.
    18. 18)
      • 13. Singh, S., Chand, S., Kumar, R., et al: ‘NEECP: a novel energy efficient clustering protocol for prolonging lifetime of WSNs’, IET Wirel. Sens. Syst., 2016, 6, (5), pp. 151–157.
    19. 19)
      • 11. Mostafaei, H., Meybodi, M., Esnaashari, M.: ‘A learning automata based area coverage algorithm for wireless sensor networks’, J. Electron. Sci. Technol., 2010, 8, (3), pp. 200–205.
    20. 20)
      • 19. Mohamadi, H., Salleh, S., Ismail, A.S.: ‘A learning automata-based solution to the priority-based target coverage problem in directional sensor networks’, Wirel. Pers. Commun., 2014, 79, pp. 2323–2338.
    21. 21)
      • 4. Bajaj, D., Manju, : ‘Maximum coverage heuristic (MCH) for target coverage problem in WSN’. Int. Advance Computing Conf., 2014, pp. 300–305.
    22. 22)
      • 22. Mostafaei, H., Esnaashari, M., Meybodi, M.R.: ‘A coverage monitoring algorithm based on learning automata for wireless sensor networks’, App. Math. Inf. Sci., 2015, 9, (3), pp. 1317–1325.
    23. 23)
      • 7. Mostafaei, H., Chowdhury, M.U., Islam, R., et al: ‘Connected P-percent coverage in wireless sensor networks based on degree constraint dominating set approach’. Proc. 18th ACM Int. Conf. Modeling, Analysis and Simulation of Wireless and Mobile Systems, Mexico, November 2015, pp. 157–160.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-wss.2017.0090
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