In wireless sensor network (WSN) target-based coverage plays a vital role in forwarding the information from source to destination via multiple sensors by covering the given targets in location specific wise. The coverage of targets and connectivity among the sensors are the two most addressable issues that are to be considered for effective data transmission. In this paper, a mathematical model called Nelder–Mead method is imposed with shuffled frog leaping algorithm for improvised local search to deploy the sensors to cover the given targets without violating the constraints in coverage as well as connectivity. The proposed algorithm is evaluated with standard performance metrics and compared with the existing algorithms and shows the significance of the proposed algorithm.
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Ananthi M, Vijayakumar K (2020a) Stock market analysis using candlestick regression and market trend prediction (CKRM). J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-01892-5
Ananthi M, Vijayakumar K (2020b) An intelligent approach for dynamic network traffic restriction using MAC address verification. Comput Commun. https://doi.org/10.1016/j.comcom.2020.02.021
Gupta SK, Kuila P, Jana PK (2015a) Genetic algorithm for k-connected relay node placement in wireless sensor networks. In: Proceedings of the second international conference on computer and communication technologies. Springer, pp 721–729
Gupta K et al (2015b) Genetic algorithm approach for k-coverage and m-connected node placement in target based wireless sensor networks. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2015.11.009
Khasteh SH, Shouraki SB, Hajiabdorahim N, Dadashnialehi E (2012) A new approach for integrated coverage and connectivity in wireless sensor networks. Comput Commun 36(1):113–120
Mansour M, Jarray F (2015) An iterative solution for the coverage and connectivity problem in wireless sensor network. Proc Comput Sci 63:494–498
Mini S, Udgata SK, Sabat SL (2012) Connected coverage problem in wireless sensor networks. ISRN Sens Netw 2012:9. https://doi.org/10.5402/2012/858021
Misra S, Kumar MP, Obaidat MS (2011) Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks. Comput Commun 34(12):1484–1496
Nithya M, Vijayakumar K (2020) Secured segmentation for ICD datasets. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-02009-8
Rebai M, Leberre M, Snoussi H, Hnaien F, Khoukhi L (2015) Sensoe deployment optimization methods to achieve both coverage and connectivity in wireless sensor networks. Comput Oper Res 59:11–21
Sun G, Liu Y, Li H, Wang A, Liang S, Zhang Y (2017) A novel connectivity and coverage algorithm based on shortest path for wireless sensor networks. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2017.10.019
Vijayakumar K, Arun C (2017) Automated risk identification using NLP in cloud-based development environments. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-017-0503-7
Zhao Q, Gurusamy M (2008) Lifetime maximization for connected target coverage in wireless sensor networks. IEEE/ACM Trans Netw 16(6):1378–1391
Zou Yi, Chakrabarty K (2005) A distributed coverage-and connectivity-centric technique for selecting active nodes in wireless sensor networks. IEEE Trans Comput 54(8):978–991
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Natarajan, P., Parthiban, L. k-coverage m-connected node placement using shuffled frog leaping: Nelder–Mead algorithm in WSN. J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-02223-4
- Target based WSN
- Shuffled frog leaping algorithm