Increasing energy efficiency of rule-based fuzzy clustering algorithms using CLONALG-M for wireless sensor networks

Date

2021-09-01

Author

Sert, Seyyit Alper
Yazıcı, Adnan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

299
views

0
downloads

Because of its efficiency, clustering is used for effective communication in Wireless Sensor Networks (WSNs). In the WSN clustering area, fuzzy approaches are found to be superior to crisp cluster counterparts when the boundaries between clusters are unclear. As a result, many studies have proposed some fuzzy-based solutions to the cluster problem in WSNs. Most rule-based fuzzy clustering systems employ field experts in trial and error processes, identifying and defining fuzzy rules as well as the forms of membership functions at the output; thus, considerable time has been allocated to realize and define these functions. Therefore, it is almost impossible or impractical to achieve a fuzzy system optimally. In this study, we propose a modified clonal selection algorithm (CLONALG-M) to improve the energy efficiency of rule-based fuzzy clustering algorithms. Although some studies in the literature focus on fuzzy optimization in general, to the best of our knowledge, performance improvement of rule-based fuzzy clustering algorithms is not taken into account. The CLONALG-M algorithm based on the Clonal Selection Principle is used to elucidate the basic principles of an adaptive immune system. In this study, we apply this principle to determine the approximate deployment of output-based membership functions that increase the performance of rule-based fuzzy clustering algorithms, whose rule base and shape of membership functions are previously known. Experimental analysis and evaluations of the proposed approach have been performed on selected fuzzy clustering approaches, and obtained results show that our approach performs and adapts well for improving performance of fuzzy output functions.

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85107035417&origin=inward
https://hdl.handle.net/11511/91132

Journal

Applied Soft Computing

DOI

https://doi.org/10.1016/j.asoc.2021.107510

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

An Energy Aware Fuzzy Unequal Clustering Algorithm for Wireless Sensor Networks Bagci, Hakan; Yazıcı, Adnan (2010-07-23) In order to gather information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. The most of the proposed clustering algorithms do not consider the location of the base station. This situation causes hot spots problem in multi-hop WSNs. Unequal clustering mechanisms, which are designed by considering the base station location, solve this problem. In this paper, we introduce a fuzzy unequal clustering algorithm (EAUCF) which aims to prolong the lifetime of WSNs. EAUCF adjusts t...
An energy aware fuzzy approach to unequal clustering in wireless sensor networks Bagci, Hakan; Yazıcı, Adnan (2013-04-01) In order to gather information more efficiently in terms of energy consumption, wireless sensor networks (WSNs) are partitioned into clusters. In clustered WSNs, each sensor node sends its collected data to the head of the cluster that it belongs to. The cluster-heads are responsible for aggregating the collected data and forwarding it to the base station through other cluster-heads in the network. This leads to a situation known as the hot spots problem where cluster-heads that are closer to the base stati...
Optimal deployment in randomly deployed heterogeneous WSNs: A connected coverage approach SEVGİ, CÜNEYT; Koçyiğit, Altan (2014-11-01) Wireless sensor networks (WSNs) are resource-scarce networks and the optimization of the resources is challenging. As far as random deployment is concerned, the optimization of these resources becomes even more difficult In this paper, a novel framework is proposed for solving optimal deployment problems for randomly deployed and clustered WSNs. In several existing approaches to solve these problems, either only partial-coverage is considered or only connectivity is analyzed when full-coverage is assured. T...
Reliable real-time video communication in wireless sensor networks Ayran, Orhan; Akan, Özgür Barış; Department of Electrical and Electronics Engineering (2007) Many wireless sensor network (WSN) applications require efficient multimedia communication capabilities. However, the existing communication protocols in the literature mainly aim to achieve energy efficiency and reliability objectives and do not address the multimedia communication challenges in WSN. In this thesis, comprehensive performance evaluation of the existing transport protocols is performed and it has been shown that the existing proposals achieve very poor performance in terms of large set of me...
Performance of transport protocols for multimedia communications in wireless sensor networks Akan, Oezguer B. (2007-10-01) Many wireless sensor network (WSN) applications require efficient multimedia communication capabilities. However, the existing communication protocols in the literature mainly aim to achieve energy efficiency and reliability objectives and do not address multimedia communication challenges in WSN. In this paper, comprehensive performance evaluation of the existing transport protocols is performed for multimedia communication in WSN. Performance metrics such as packet delivery rate, end-to-end packet delay, ...

Citation Formats

S. A. Sert and A. Yazıcı, “Increasing energy efficiency of rule-based fuzzy clustering algorithms using CLONALG-M for wireless sensor networks,” Applied Soft Computing, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85107035417&origin=inward.