Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
An Energy Aware Fuzzy Unequal Clustering Algorithm for Wireless Sensor Networks
Date
2010-07-23
Author
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
218
views
0
downloads
Cite This
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 the cluster-head radius considering the residual energy and the distance to the base station parameters of the sensor nodes. This helps decreasing the intra-cluster work of the sensor nodes which are closer to the base station or have lower battery level. We utilize fuzzy logic for handling the uncertainties in cluster-head radius estimation. We compare our algorithm with some popular algorithms in literature, namely LEACH, CHEF and EEUC, according to First Node Dies (FND), Half of the Nodes Alive (HNA) and energy-efficiency metrics. Our simulation results show that EAUCF performs better than the other algorithms in most of the cases. Therefore, EAUCF is a stable and energy-efficient clustering algorithm to be utilized in any real time WSN application.
URI
https://hdl.handle.net/11511/53477
Conference Name
2010 IEEE World Congress on Computational Intelligence
Collections
Department of Computer Engineering, Conference / Seminar
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...
Increasing energy efficiency of rule-based fuzzy clustering algorithms using CLONALG-M for wireless sensor networks
Sert, Seyyit Alper; Yazıcı, Adnan (2021-09-01)
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 ...
An Efficient Fuzzy Path Selection Approach to Mitigate Selective Forwarding Attacks in Wireless Sensor Networks
Sert, Seyyit Alper; Fung, Carol; George, Roy; Yazıcı, Adnan (2017-07-12)
Wireless Sensor Networks (WSNs) facilitate efficient data gathering requirements occurring in indoor and outdoor environments. A great deal of WSNs operates by sensing the area-of-interest (AOI) and transmitting the obtained data to a sink/(s). The transmitted data is then utilized in decision making processes. In this regard, security of raw and relayed data is both crucial and susceptible to malicious attempts targeting the task of the network which occurs on the wireless transmission medium. A node, when...
Analysis and modeling of routing and security problems in wireless sensor networks with mathematical programming
İncebacak, Davut; Baykal, Nazife; Bıçakcı, Kemal; Department of Information Systems (2013)
Wireless Sensor Networks (WSNs) are composed of battery powered small sensor nodes with limited processing, memory and energy resources. Self organization property together with infrastructureless characteristics of WSNs make them favorable solutions for many applications. Algorithms and protocols developed for WSNs must consider the characteristics and constraints of WSNs but since battery replenishment is not possible or highly challenging for sensor nodes, one of the major concerns in designing network p...
A Framework for Energy based Performability models for Wireless Sensor Networks
Omondi, Fredrick A.; Shah, Purav; Gemikonakli, Orhan; Ever, Enver (2015-03-27)
A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. Active/Sleep operation modes have also be...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. Bagci and A. Yazıcı, “An Energy Aware Fuzzy Unequal Clustering Algorithm for Wireless Sensor Networks,” presented at the 2010 IEEE World Congress on Computational Intelligence, Barcelona, SPAIN, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53477.