Welcome to the InfoSci Platform
Reference Hub9
A Resilient Steady Clustering Technique for Sensor Networks

A Resilient Steady Clustering Technique for Sensor Networks

Khushboo Jain, Anoop Kumar, Vaibhav Vyas
Copyright: © 2020 |Volume: 11 |Issue: 4 |Pages: 12
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781799806240|DOI: 10.4018/IJAEC.2020100101
Cite Article Cite Article

MLA

Jain, Khushboo, et al. "A Resilient Steady Clustering Technique for Sensor Networks." IJAEC vol.11, no.4 2020: pp.1-12. http://doi.org/10.4018/IJAEC.2020100101

APA

Jain, K., Kumar, A., & Vyas, V. (2020). A Resilient Steady Clustering Technique for Sensor Networks. International Journal of Applied Evolutionary Computation (IJAEC), 11(4), 1-12. http://doi.org/10.4018/IJAEC.2020100101

Chicago

Jain, Khushboo, Anoop Kumar, and Vaibhav Vyas. "A Resilient Steady Clustering Technique for Sensor Networks," International Journal of Applied Evolutionary Computation (IJAEC) 11, no.4: 1-12. http://doi.org/10.4018/IJAEC.2020100101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In wireless sensor networks (WSNs), each sensor node is proficient to transmit data packets dynamically deprived of any constraint of fixed infrastructure. Sensor nodes (SNs) intermittently travels within the network from one cluster to another, which makes the network topology unsteady, uncertain, and unreliable. Consequently, it turns to be an immense challenge to sustain network stability and durability. In this work, the authors have presented a resilient steady clustering technique (RSCT) that will maintain durability and steadiness to the sensor network by reducing the unnecessary and avoidable cluster head (CH) changes and minimizing clustering and networking overheads. In the presented technique, they have introduced a new SN that acts as a standby node (SBN) in the cluster. This SBN performs the tasks of CH whenever the actual CH moves from the cluster. Later the CH re-elect the new SBN. This process keeps the network available and serviceable without any interruption. The decision for selecting the CH and SBN depends on the optimal CH threshold function and an energy threshold function.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.