A novel data aggregation using multi objective based male lion optimization algorithm (DA-MOMLOA) in wireless sensor network

Wireless sensor network efficiently aggregates and transmits data in an internet of things (IoT) environment. Machine Learning algorithms can minimize data transmission rates by utilizing the distributive features of the network. This study proposes a novel cluster-based data aggregation method usin...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing 2022-12, Vol.13 (12), p.5645-5653
Main Authors: Saranraj, G., Selvamani, K., Malathi, P.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Clusters
Communication
Computational Intelligence
Data management
Data transmission
Energy consumption
Energy efficiency
Engineering
Genetic algorithms
Internet of Things
Literature reviews
Machine learning
Males
Multiple objective analysis
Optimization
Original Research
Robotics and Automation
Sensors
Transmission rate (communications)
User Interfaces and Human Computer Interaction
Wireless sensor networks
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Summary:Wireless sensor network efficiently aggregates and transmits data in an internet of things (IoT) environment. Machine Learning algorithms can minimize data transmission rates by utilizing the distributive features of the network. This study proposes a novel cluster-based data aggregation method using multi-objective based male lion optimization algorithm (DA-MOMLOA) for evaluating the network based on energy, delay, density and distance. The data aggregation method is employed with the help of cluster head wherein data aggregated from similar clusters are forwarded to the sink node following by application of machine learning algorithms. Hence, the proposed method shows promising results as it significantly increases the network efficiency and reduces the packet drop owing to a smaller number of aggregation processes.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-021-03230-9