A novel data aggregation using multi objective based male lion optimization algorithm (DA-MOMLOA) in wireless sensor network
| Autor: | K. Selvamani, P. Malathi, G. Saranraj |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
020203 distributed computing
General Computer Science Computer science Network packet Node (networking) Real-time computing 020206 networking & telecommunications Computational intelligence 02 engineering and technology Data aggregator 0202 electrical engineering electronic engineering information engineering Cluster (physics) Wireless sensor network Energy (signal processing) Data transmission |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing. 13:5645-5653 |
| ISSN: | 1868-5145 1868-5137 |
| DOI: | 10.1007/s12652-021-03230-9 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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