Multi-layer Uneven Clustering for Wireless Sensor Networks
Lecture Notes in Electrical Engineering, ISSN: 1876-1119, Vol: 808 LNEE, Page: 1240-1249
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Wireless sensor networks need simple and effective algorithms to promote the lifetime of these energy limit networks. This article proposed a clustering algorithm: MLUC. We divide the whole network into several layers, and each layer is divided into a number of clusters. A cluster head receive data in the cluster, forwards the data to other cluster head in another layer. Cluster heads forward data one by one and send data to sink node at last. From the perspective of reducing the forwarded data energy consumption of cluster heads, we resolve the number and size of layers. Each layer is divided into a number of clusters. From the perspective of minimizing energy consumption including data awareness, sending, receiving and other energy consumption in a layer, the number of clusters in a layer is determined. Because the cluster numbers of layers are not the same, area covered by a cluster is different to balance the energy consumption in different layers. Simulation results show that the algorithm can prolong the lifetime of networks which are unable to obtain node residual energy and location.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85120065986&origin=inward; http://dx.doi.org/10.1007/978-981-16-6554-7_138; https://link.springer.com/10.1007/978-981-16-6554-7_138; https://dx.doi.org/10.1007/978-981-16-6554-7_138; https://link.springer.com/chapter/10.1007/978-981-16-6554-7_138
Springer Science and Business Media LLC
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