http://iet.metastore.ingenta.com
1887

Genetic algorithm-based meta-heuristic for target coverage problem

Genetic algorithm-based meta-heuristic for target coverage problem

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Wireless Sensor Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In wireless sensor networks (WSNs), network lifetime and energy consumption are two important parameters which directly impacts each other. In order to enhance the global network lifetime, one should need to utilise the available sensors’ energy in an optimise way. There are several approaches discussed in the literature to maximise the network lifetime for well-known target coverage problem in WSN. The target coverage problem is presented as a maximum network lifetime problem (MLP) and solved heuristically using various approaches. In this study, the authors propose a genetic algorithm (GA)-based meta-heuristic to solve the above said MLP. The GA is a non-linear optimisation solution method which is proven to be better as compared to the column generation or approximation schemes.

References

    1. 1)
      • 1. Chong, C.-Y., Kumar, S.: ‘Sensor networks: evolution, opportunities, and challenges’, Proc. IEEE, 2003, 91, (8), pp. 12471256.
    2. 2)
      • 2. Slijepcevic, S., Potkonjak, M.: ‘Power efficient organization of wireless sensor networks’. Proc. of the IEEE Int. Conf. on Communications, Helsinki, Finland, 2001, pp. 472476.
    3. 3)
      • 3. Cardei, M., Thai, M.T., Li, Y., et al: ‘Energy-efficient target coverage in wireless sensor networks’. Proc. of the 24th Conf. of the IEEE Communications Society, Miami, USA, 2005, vol. 3, pp. 19761984.
    4. 4)
      • 4. Mini, S., Udgata, S.K., Sabat, S.L.: ‘A heuristic to maximize network lifetime for target coverage problem in wireless sensor networks’, Ad Hoc Sens. Wirel. Netw., 2011, 13, pp. 251269.
    5. 5)
      • 5. Mostafaei, H., Montieri, A., Persico, V., et al: ‘A sleep scheduling approach based on learning automata for WSN partial coverage’, J. Netw. Comput. Appl., 2017, 80, pp. 6778.
    6. 6)
      • 6. Mostafaei, H., Meybodi, M.R.: ‘Maximizing lifetime of target coverage in wireless sensor networks using learning automata’, Wirel. Pers. Commun., 2013, 71, (2), pp. 14611477.
    7. 7)
      • 7. Mostafaei, H., Esnaashari, M., Meybodi, M.R.: ‘A coverage monitoring algorithm based on learning automata for wireless sensor networks’, Appl. Math. Inf. Sci., 2015, 9, (3), pp. 13171325.
    8. 8)
      • 8. Pujari, A.K., Mini, S., Padhi, T., et al: ‘Polyhedral approach for lifetime maximization of target coverage problem’. Proc. of the Int. Conf. on Distributed Computing and Networking, Turku, Finland, 2015, pp. 14.114.8.
    9. 9)
      • 9. Manju Chand, S., Kumar, B.: ‘Maximizing network lifetime for target coverage problem in wireless sensor networks’, IET Wirel. Sens. Syst., 2016, 77, (3), pp. 21172139.
    10. 10)
      • 10. 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. 151157.
    11. 11)
      • 11. Chaudhary, M., Pujari, A.K.: ‘Q-coverage problem in wireless sensor networks’. Proc. Int. Conf. Distributed Computing Networking, Hydearbad, india, 2009, pp. 325330.
    12. 12)
      • 12. Castaño, F., Rossi, A., Sevaux, M., et al: ‘A column generation approach to extend lifetime in wireless sensor networks with coverage and connectivity constraints’, Comput. Oper. Res., 2014, 52, (B), pp. 220230.
    13. 13)
      • 13. Singh, S., Chand, S., Kumar, B.: ‘Heterogeneous HEED protocol for wireless sensor networks’, Wirel. Pers. Commun., 2014, 77, (3), pp. 21172139.
    14. 14)
      • 14. Gentili, M., Raiconi, A.: ‘Alpha-coverage to extend network lifetime on wireless sensor networks’, Optimum Lett., 2013, 7, (1), pp. 157172.
    15. 15)
      • 15. Gupta, S.K., Kuilab, P., Jana, P.K.: ‘Genetic algorithm approach for k-coverage and m-connected node placement in target based wireless sensor networks’, Comput. Electr. Eng., 2016, 56, pp. 544556.
    16. 16)
      • 16. Carrabs, F., Cerulli, R., D'Ambrosio, C., et al: ‘A hybrid exact approach for maximizing lifetime in sensor networks with complete and partial coverage constraints’, J. Netw. Comput. Appl., 2015, 58, pp. 1222.
    17. 17)
      • 17. Raiconi, A., Gentili, M.: ‘Exact and metaheuristic approaches to extend lifetime and maintain connectivity in wireless sensors networks’, ‘Lecture notes in computer science’, vol. 6701 (Springer, Berlin/Heidelberg, 2011), pp. 607619.
    18. 18)
      • 18. Zhang, H., Hou, J.C.: ‘Maximizing α-lifetime for wireless sensor networks’, Int. J. Sens. Netw., 2006, 1, (1), pp. 6471.
    19. 19)
      • 19. Yoon, Y., Kim, Y.-H.: ‘An efficient genetic algorithm for maximum coverage deployment in wireless sensor networks’, IEEE Trans. Cybern., 2013, 43, (5), pp. 14731483.
    20. 20)
      • 20. Rebai, M., Leberre, M., Snoussi, H., et al: ‘Sensor deployment optimization methods to achieve both coverage and connectivity in wireless sensor networks’, Comput. Oper. Res., 2015, 59, pp. 1121.
    21. 21)
      • 21. Konak, A., Coit, D.W., Smith, A.E.: ‘Multi-objective optimization using genetic algorithms: a tutorial’, Reliab. Eng. Syst. Saf., 2006, 91, (9), pp. 9921007.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-wss.2017.0067
Loading

Related content

content/journals/10.1049/iet-wss.2017.0067
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address