Fuzzy-based Firefly and ACO Algorithm for Densely Deployed WSN

  • Tripti Sharma Maharaja Surajmal Institute of Technology/Indira Gandhi Delhi Technical University for Women
  • Amar Kumar Mohapatra Indira Gandhi Delhi Technical University for Women
  • Geetam Tomar Rajkiya Engineering College

Abstract

Most of the wireless sensor networks (WSNs) used in healthcare and security sectors are affected by the battery constraints, which cause a low network lifetime problem and prevents these networks from achieving their maximum performance. It is anticipated that by combining fuzzy logic (FL) approximation reasoning approach with WSN, the complex behavior of WSN will be easier to handle. In healthcare, WSNs are used to track activities of daily living (ADL) and collect data for longitudinal studies. It is easy to understand how such WSNs could be used to violate people’s privacy. The main aim of this research is to address the issues associated with battery constraints for WSN and resolve these issues. Such an algorithm could be successfully applied to environmental monitoring for healthcare systems where a dense sensor network is required and the stability period should be high.

Keywords

clustering, firefly, WSN, ant colony optimization, fuzzy, wireless sensor healthcare network, FIS,

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Published
Jun 17, 2022
How to Cite
SHARMA, Tripti; MOHAPATRA, Amar Kumar; TOMAR, Geetam. Fuzzy-based Firefly and ACO Algorithm for Densely Deployed WSN. Computer Assisted Methods in Engineering and Science, [S.l.], june 2022. ISSN 2299-3649. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/438>. Date accessed: 28 june 2022. doi: http://dx.doi.org/10.24423/cames.438.
Section
[CLOSED]Scientific Computing and Learning Analytics for Smart Healthcare Systems