Hybrid artificial bee colony and glow worm algorithm for energy efficient cluster head selection in wireless sensor networks. (9th September 2021)
- Record Type:
- Journal Article
- Title:
- Hybrid artificial bee colony and glow worm algorithm for energy efficient cluster head selection in wireless sensor networks. (9th September 2021)
- Main Title:
- Hybrid artificial bee colony and glow worm algorithm for energy efficient cluster head selection in wireless sensor networks
- Authors:
- Kaur, Jasleen
Rani, Punam
Dahiya, Brahm Prakash - Abstract:
- Abstract : Purpose: This paper aim to find optimal cluster head and minimize energy wastage in WSNs. Wireless sensor networks (WSNs) have low power sensor nodes that quickly lose energy. Energy efficiency is most important factor in WSNs, as they incorporate limited sized batteries that would not be recharged or replaced. The energy possessed by the sensor nodes must be optimally used so as to increase the lifespan. The research is proposing hybrid artificial bee colony and glowworm swarm optimization [Hybrid artificial bee colony and glowworm swarm optimization (HABC-GSO)] algorithm to select the cluster heads. Previous research has considered fitness-based glowworm swarm with Fruitfly (FGF) algorithm, but existing research was limited to maximizing network lifetime and energy efficiency. Design/methodology/approach: The proposed HABC-GSO algorithm selects global optima and improves convergence ratio. It also performs optimal cluster head selection by balancing between exploitation and exploration phases. The simulation is performed in MATLAB. Findings: The HABC-GSO performance is evaluated with existing algorithms such as particle swarm optimization, GSO, Cuckoo Search, Group Search Ant Lion with Levy Flight, Fruitfly Optimization algorithm and grasshopper optimization algorithm, a new FGF in the terms of alive nodes, normalized energy, cluster head distance and delay. Originality/value: This research work is original.
- Is Part Of:
- World journal of engineering. Volume 19:Number 2(2022)
- Journal:
- World journal of engineering
- Issue:
- Volume 19:Number 2(2022)
- Issue Display:
- Volume 19, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 19
- Issue:
- 2
- Issue Sort Value:
- 2022-0019-0002-0000
- Page Start:
- 147
- Page End:
- 156
- Publication Date:
- 2021-09-09
- Subjects:
- Particle swarm optimization -- Glowworm swarm optimization -- Cuckoo search -- Grasshopper optimization algorithm
Engineering -- Periodicals
620 - Journal URLs:
- http://www.emeraldinsight.com/ ↗
http://www.emeraldinsight.com/journal/wje ↗ - DOI:
- 10.1108/WJE-03-2021-0170 ↗
- Languages:
- English
- ISSNs:
- 1708-5284
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25849.xml