Research Area: Wireless Sensor Networks
In this paper, we proposed an approach to clustering based on bio-inspired behaviour and distributed energy efficient model. The motivation to propose this clustering approach is due to the challenge of performance in terms of finding an efficient way to send data packets to base stations and to maintain the lifetime performance of wireless sensor networks. The bioinspired approach adopted the behaviour of a bird called Kestrel. This behaviour is expressed using mathematical formulation and then translated into an algorithm. The bio-inspired algorithm is combined with the distributed energy efficient model for clustering to ensure efficient energy optimization. The proposed clustering approach, referred to as DEEC-KSA, is evaluated through simulation and compared with benchmarked clustering algorithms. The result of simulation showed that the performance of DEEC-KSA is efficient among the comparative clustering algorithms for energy optimization in terms of stability period, network lifetime and network throughput. Additionally, the proposed DEEC-KSA has the optimal time (in seconds) to send packets to base station successfully.
Keywords:
load balancing
wireless sensor network
clustering algorithm
kestrel-based search algorithm
heterogeneous environment
Author(s) Name: Israel Edem Agbehadji; Richard C. Millham; Simon James Fong; Jason J. Jung; Khac-Hoai Nam Bui; Abdultaofeek Abayomi; Samuel Ofori Frimpong
Journal name:
Conferrence name: International Conference on Wireless Networks and Mobile Communications (WINCOM)
Publisher name: IEEE
DOI: 10.1109/WINCOM47513.2019.8942532
Volume Information:
