Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics
DOI:
https://doi.org/10.4108/eai.13-7-2018.165522Keywords:
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)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).
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 EAI Endorsed Transactions on Energy Web
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
This is an open-access article distributed under the terms of the Creative Commons Attribution CC BY 3.0 license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.