Research Article
Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics
@ARTICLE{10.4108/eai.13-7-2018.165522, author={Murali Subramanian and Jaisankar Natarajan and Rajkumar Rajasekaran}, title={Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics}, journal={EAI Endorsed Transactions on Energy Web}, volume={8}, number={31}, publisher={EAI}, journal_a={EW}, year={2020}, month={7}, keywords={Air pollution, Bandwidth allocation, optimal path, Energy, Cluster head selection, Cuckoo Search Algorithm (CSA), Distributed Wireless Sensor Cluster Algorithm (DWCA), Improved Artificial Swarm Optimization Algorithm (IASA)}, doi={10.4108/eai.13-7-2018.165522} }- Murali Subramanian
Jaisankar Natarajan
Rajkumar Rajasekaran
Year: 2020
Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics
EW
EAI
DOI: 10.4108/eai.13-7-2018.165522
Abstract
The most debated phenomena of the 21st century which might change the global landscape for living organisms. The same phenomena could even threaten climate pattern. Because of this, the earth may experience a highly unstable natural disaster like flooding, cyclone, earthquake, tsunami, severe drought and inhabitant environment like the highly polluted atmosphere, intolerable rise in temperature, acid rain, etc, This issue is solved in this research work by the introduction of the technique referred to as the Air pollution monitoring system with Swarm Intelligence (CASI-CSA-IAFSA) that will do the clustering of sensor nodes and the assortment of sensor nodes. Then the aggregated data would transmit the optimal route to the base station designated employing the artificial fish swarm technique. The proposed research technique by the introduction of the strategy referred to as the bandwidth allocation aware Air pollution monitoring system with cuckoo and fish swarm approach (BA-APMS-CSFSO).
Copyright © 2020 Murali Subramanian et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
