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Cluster Centroid-Based Energy Efficient Routing Protocol for WSN-Assisted IoT

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Cluster Centroid-Based Energy Efficient Routing Protocol for WSN-Assisted IoT

Volume 5, Issue 4, Page No 296–313, 2020

Author’s Name: Nalluri Prophess Raj Kumar*Email, Josemin Bala Gnanadhas
Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, 641114, India
*whom correspondence should be addressed. E-mail: nalluriprophess@karunya.edu.in

Adv. Sci. Technol. Eng. Syst. J. 5(4), 296–313 (2020); crossref symbol DOI: 10.25046/aj050436

Keywords: Internet of Things, Wireless sensor networks, Energy management, Basestation, Clustering, Energy Centroid

Received: 31 May 2020, Accepted: 19 July 2020, Published Online: 28 July 2020
(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Network Engineering (ENW))
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Abstract

Wireless sensor network is highly resource constrained, where energy efficiency and network lifetime plays a major role for its sustenance. As the sensor nodes are battery operated and deployed in hostile environments, either recharging or replacement of batteries in sensor nodes is not possible after its deployment in inaccessible areas. In such condition, energy is the vital factor for the survival of sensor node in the sensing field. In order to increase the network lifetime and balance the energy consumption, robust routing protocols are required. The proposed network routing has three phases: 1. Network initiation phase to create a zone which enables the communication among local nodes 2. Zone co-ordinator selection phase algorithm to form zone cluster and its re-election procedure and 3. Zone head selection with its replacement phase based on energy centroid positional information and distance to the basestation to distribute load equally among zone co-ordinators, local sensor nodes. The data path between zone heads and basestation is distance centric and is optimized at one hop and dual hop levels to avoid data packet loss at zoneheads. Each zone is designed to own atmost ¼ rth of deployed sensor node count through uniform random deployment. Simulations results when basestation is placed inside sensing field indicates that the proposed network algorithm outperforms when benchmarked against similar protocols like conventional LEACH, Traditional PEGASIS, existing PRRP, ES3 protocols in terms of performance metrics like Network energy consumption, Average energy consumed by sensor node, Packet delivery ratio, Packet loss percentage and Network throughput.

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  64. Tanveer Ahmed, Muhammad Kaleem, Khurram Saleem Alimgeer, Mustafa Shakir, Sajid Nazir, "Optimization of Depth-Based Routing for Underwater Wireless Sensor Networks through Intelligent Assignment of Initial Energy", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1799–1803, 2017. doi: 10.25046/aj0203219
  65. Anum Mehmood, M. Usman Akram, Anum Tariq, Ayesha Fatima, "A Comparison of Mean Models and Clustering Techniques for Vertebra Detection and Region Separation from C-Spine X-Rays", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1758–1770, 2017. doi: 10.25046/aj0203215
  66. Diego Peluffo-Ordóñez, Paul Rosero-Montalvo, Ana Umaquinga-Criollo, Luis Suárez-Zambrano, Hernan Domínguez-Limaico, Omar Oña-Rocha, Stefany Flores-Armas, Edgar Maya-Olalla, "Theoretical developments for interpreting kernel spectral clustering from alternative viewpoints", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1670–1676, 2017. doi: 10.25046/aj0203208
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