A new dynamic weight clustering algorithm for wireless sensor networks

Essa, Alsnousi; Al-Dubai, Ahmed; Romdhani, Imed; Eshaftri, Mohamed

Abstract

Since sensor nodes have limited energy resources, prolonging network lifetime and improving scalability are essential elements in energy-efficient Wireless Sensor Networks (WSNs). Most existing approaches consider the residual energy of a single node when electing a cluster head (CH), omitting other factors associated with the node, such as its location within hte WSN topology and its nodal degree. Thus, this paper proposes a new Dynamic Weight Clustering based Algorithm (DWCA) for WSNs to reduce the overall energy consumption, balance the energy consumption among all noces and improve the network scalability. The study has examined the performance of the proposed DWCA algorithm using simulation experiments. We copare the performance of our DWCA against some counterparts. The results demonstrate that our algorithm outperforms its counterparts in terms of energy efficiencey and scalability.

Citation

Essa, A., Al-Dubai, A., Romdhani, I., & Eshaftri, M. (2017). A new dynamic weight clustering algorithm for wireless sensor networks. In S. Yang, J. Gao, Y. Zhang, K. Yang, V. C. M. Leung, & J. Hu (Eds.), Smart Grid Inspired Future Technologies: First International Conference, Liverpool, UK, May 19-20, 2016 SmartGIFT 2016 (195-203)

• Conference Name: 1st EAI International Conference on Smart Grid Inspired Future Technologies (SmartGift 2016)
• Start Date: May 19, 2016
• End Date: May 20, 2016
• Acceptance Date: May 19, 2016
• Publication Date: 2017
• Deposit Date: Jul 7, 2016
• Peer Reviewed: Peer Reviewed
• Pages: 195-203
• Series Title: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Series ISSN: 1867-8211
• Book Title: Smart Grid Inspired Future Technologies: First International Conference, Liverpool, UK, May 19-20, 2016 SmartGIFT 2016
• ISBN: 978-3-319-47729-9, 978-3-319-47728-2
• Keywords: Wireless sensor network, routing, topology, cluster head, energy-efficiency
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/10314