FFMCP: Feed-Forward Multi-Clustering Protocol Using Fuzzy Logic for Wireless Sensor Networks (WSNs)

Pankaj Kumar Mishra and Shashi Kant Verma
Additional contact information
Pankaj Kumar Mishra: Department of Computer Engineering, College of Technology, Uttarakhand 263145, India
Shashi Kant Verma: Department of Computer Engineering, G.B.P.E.C., Pauri Garhwal, Uttrakhand 263145, India

Energies, 2021, vol. 14, issue 10, 1-21

Abstract: The restriction on the battery life of sensors is a bottleneck for wireless sensor networks (WSNs). This paper proposes a new feed-forward multi-clustering protocol (FFMCP) to boost the network lifetime. The utilization of fuzzy logic helps to overcome the uncertainties in the value of input parameters. The proposed protocol selects the most suitable cluster heads (CHs) using the multi-clustering method. A multi-clustering technique is defined utilizing the node’s information of the previous round and a fuzzy inference system to decide the CHs. The sensor nodes spend energy due to non-uniform CH distribution and long-distance data transmission by member nodes. The main focus of the proposed protocol is to reduce the member node distance. Our proposal distributes CH nodes uniformly using unequal clustering. The simulation outcome reveals that the proposed algorithm(FFMCP) has better performance in terms of tenth node death (TND), half node death (HND), remaining energy after 800 rounds (E_800), and average energy spent per round (AVG_PR) as compared to standard clustering schemes in the past.

Keywords: multi-clustering protocol; wireless sensor network; fuzzy inference system; unequal clustering (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/10/2866/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/10/2866/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:10:p:2866-:d:555505

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().