A location-based clustering algorithm for data gathering in 3D underwater Wireless Sensor Networks

Author(s):  
K.R. Anupama ◽  
Aparna Sasidharan ◽  
Supriya Vadlamani
Sensors ◽  
2016 ◽  
Vol 16 (3) ◽  
pp. 404 ◽  
Author(s):  
Mariam Akbar ◽  
Nadeem Javaid ◽  
Ayesha Khan ◽  
Muhammad Imran ◽  
Muhammad Shoaib ◽  
...  

2020 ◽  
Vol 16 (2) ◽  
pp. 155014771990011 ◽  
Author(s):  
G Pius Agbulu ◽  
G Joselin Retna Kumar ◽  
A Vimala Juliet

Despite unique energy-saving dispositions of cluster-based routing protocols, clustered wireless sensor networks with static sinks typically have problems of unbalanced energy consumptions, as the cluster head nodes around the sink are typically loaded with traffic from upper levels of clusters. This results in reduced lifetimes of the nodes and deterioration of other crucial performances. Meanwhile, it has been inferred from current literature that dedicated relay cooperation in cluster-based wireless sensor networks guarantees longer lifetime of the nodes and more improved performance. Therefore, to attain further enhanced performance among the current schemes, a lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks is proposed in this article. The proposed lifetime-enhancing cooperative data gathering and relaying algorithm shares the nodes into clusters using a hybrid K-means clustering algorithm that combines K-means clustering and Huffman coding algorithms. It makes full use of dedicated relay cooperative multi-hop communication with network coding mechanisms to achieve reduced data propagation cost from the various cluster sections to the central base station. The relay node selection is framed as a NP-hard problem, with regard to communication distances and residual energy metrics. Furthermore, to resolve the problem, a gradient descent algorithm is proposed. Simulation results endorse the proposed scheme to outperform related schemes in terms of latency, lifetime, and energy consumption and delivery rates.


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