Development of Wireless Sensor Networks lifespan using Hybrid Glowworm Swarm Optimization

Little micro-electrical automaticschemes that are deployed in collecting and broadcasting data from ambience are Wireless Sensor Networks (WSNs). Providing security and energy consumptions are the most emerging issues in Wireless sensor network communication. To enhance the lifespan of a network, en...

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Bibliographic Details
Published inNeuroQuantology Vol. 20; no. 11; p. 508
Main Authors Deepakraj, D, Raja, K, Ayyasamy, A
Format Journal Article
LanguageEnglish
Published Bornova Izmir NeuroQuantology 01.01.2022
Subjects
Algorithms
Ambience
Communication
Energy consumption
Energy efficiency
Life span
Localization
Nodes
Optimization
Optimization algorithms
Optimization techniques
Power consumption
Sensors
Wireless communications
Wireless sensor networks
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Summary:Little micro-electrical automaticschemes that are deployed in collecting and broadcasting data from ambience are Wireless Sensor Networks (WSNs). Providing security and energy consumptions are the most emerging issues in Wireless sensor network communication. To enhance the lifespan of a network, energy efficiency should be increased by decreasing energy consumption of the sensor nodes, thus striking a balance in the power consumption of each node. As the primary source of origin of energy consumption of sensor nodes is long distance transmission of data, good impact on energy consumption can be provided through an efficient routing protocol. So as to enhance the lifespan of a network, a number of protocols have been put forth in the form of optimization algorithms. This study involves Glowworm Swarm Optimization (GSO). In GSO, a probabilistic cost is computed by every glowworm in spite offinding its neighboring glowworm that has theenhanced luciferin intensity than others.
ISSN:1303-5150
DOI:10.14704/nq.2022.20.11.NQ66053