MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks

Date

2015-05-01

Author

SERT, SEYYİT ALPER
Bagci, Hakan
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

250
views

0
downloads

This study introduces a new clustering approach which is not only energy-efficient but also distribution-independent for wireless sensor networks (WSNs). Clustering is used as a means of efficient data gathering technique in terms of energy consumption. In clustered networks, each node transmits acquired data to a cluster-head which the nodes belong to. After a cluster-head collects all the data from all member nodes, it transmits the data to the base station (sink) either in a compressed or uncompressed manner. This data transmission occurs via other cluster-heads in a multi-hop network environment. As a result of this situation, cluster-heads close to the sink tend to die earlier because of the heavy inter-cluster relay. This problem is named as the hotspots problem. To solve this problem, some unequal clustering approaches have already been introduced in the literature. Unequal clustering techniques generate clusters in smaller sizes when approaching the sink in order to decrease intra-cluster relay. In addition to the hotspots problem, the energy hole problem may also occur because of the changes in the node deployment locations. Although a number of previous studies have focused on energy-efficiency in clustering, to the best of our knowledge, none considers both problems in uniformly and non-uniformly distributed networks. Therefore, we propose a multi-objective solution for these problems. In this study, we introduce a multi-objective fuzzy clustering algorithm (MOFCA) that addresses both hotspots and energy hole problems in stationary and evolving networks. Performance analysis and evaluations are done with popular clustering algorithms and obtained experimental results show that MOFCA outperforms the existing algorithms in the same set up in terms of efficiency metrics, which are First Node Dies (FND), Half of the Nodes Alive (HNA), and Total Remaining Energy (TRE) used for estimating the lifetime of the WSNs and efficiency of protocols.

Subject Keywords

Wireless sensor networks, Unequal clustering, Multi-objective, Fuzzy logic

URI

https://hdl.handle.net/11511/48020

Journal

APPLIED SOFT COMPUTING

DOI

https://doi.org/10.1016/j.asoc.2014.11.063

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

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...
Multi-objective evolutionary routing protocol for efficient coverage in mobile sensor networks Attea, Bara'a A.; Khalil, Enan A.; Coşar, Ahmet (2015-10-01) Individual sensors in wireless mobile sensor networks (MSNs) can move in search of coverage region for the sensing accuracy and for reaching the most efficient topology. Besides, sensors' clustering is crucial for achieving an efficient network performance. Although MSNs have been an area of many research efforts in recent years, integrating the coverage problem of MSNs with the efficient routing requirement that will maximize the network lifetime is still missing. In this paper, we consider the coverage op...
Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications Ozdin, Ali Nail; Yazıcı, Adnan; KOYUNCU, Murat (2019-01-01) This study aims to increase the reliability of activity detection in Wireless Multimedia Sensor Networks (WMSNs) by using Semantic Web technologies extended with fuzzy logic. The proposed approach consists of three layers: the sensor layer, the data layer, and the Semantic Web layer. The sensor layer comprises a WMSN comprising sensor nodes with multimedia and scalar sensors. The data layer retrieves and stores data from the sink of WMSN. At the top of the architecture, there is a semantic web layer that in...
An Efficient Fuzzy Fusion-Based Framework for Surveillance Applications in Wireless Multimedia Sensor Networks Sert, Seyyit Alper; Yazıcı, Adnan; Coşar, Ahmet; Yilmazer, Cengiz (2014-08-08) This study is focused on a new approach for addressing the trade-off between accuracy and energy-efficiency of Wireless Multimedia Sensor Networks. Although a number of previous studies have focused on various special topics in Wireless Multimedia Sensor Networks in detail, to best of our knowledge, none presents a fuzzy multi-modal data fusion system, which is light-weight and provides a high accuracy ratio. Especially, multi-modal data fusion targeting surveillance applications make it inevitable to work ...
Path planning and localization for mobile anchor based wireless sensor networks Erdemir, Ecenaz; Tuncer, Temel Engin; Department of Electrical and Electronics Engineering (2017) In wireless sensor networks, sensors with limited resources are distributed in a wide area. Localizing the sensors is an important problem. Anchor nodes with known positions are used for sensor localization. A simple and efficient way of generating anchor nodes is to use mobile anchors which have built-in GPS units. In this thesis, a single mobile anchor is used to traverse the region of interest to communicate with the sensor nodes and identify their positions. Therefore planning the best trajectory for th...

Citation Formats

S. A. SERT, H. Bagci, and A. Yazıcı, “MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks,” APPLIED SOFT COMPUTING, pp. 151–165, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48020.