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RETRACTED: Genetic algorithm-based data controlling method using IoT-enabled WSN in power grid (Retracted Article)
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DOI：10.1007/s00500-022-07186-6.png)
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Abstract
En 中文
Internet of Things (IoT)-enabled Wireless Sensor Networks is not only an encouraging research domain but also a promising industrial trend which permits the development of various IoT-based applications, ranging from industry to education and military to agriculture. The IoT device plays a significant role in various IoT-based networks and working of such network depends upon the battery power. Once the devices have deployed in the hostile environments, replacement of batteries is not feasible. To address this, challenge a plethora of research has been conducted but IoT networks still suffer one or the other way. In this paper, a genetic algorithm is integrated with an efficient clustering for power grid application where monitoring and controlling process is proposed by using movable sinks in IoT-enabled HWSNs (OptiGeA) . The OptiGeA protocol is depicted for cluster heads election by joining the factor of density, distance, energy and heterogeneous node's capacity for its created fitness function. The investigation analysis of OptiGeA is prepared to work with single sink, multiple static sinks and multiple movable sinks to have an unslanted comparative assessment. The novel deployment technique and multiple mobile sinks approaches are proposed to shorten transmission distance between the sink and CH during system operation and pact with the hotspot issue. It is evident from a simulation study that the proposed OptiGeA protocol outflank state-of-the-art protocols on determinations of particular execution measurements precisely stability period, system's residual energy, network lifetime, throughput, and number of clusters per round execution.
Keywords:
Internet of Things
Wireless sensor networks
Genetic algorithm
Clustering
Mobile sinks
Journal
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2.5
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Citations:
2.1W