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Analytical network process based optimum cluster head selection in wireless sensor network
- Source :
- PLoS ONE, Vol 12, Iss 7, p e0180848 (2017), PLoS ONE
- Publication Year :
- 2017
- Publisher :
- Public Library of Science (PLoS), 2017.
-
Abstract
- Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.
- Subjects :
- Computer science
Distributed computing
Social Sciences
lcsh:Medicine
02 engineering and technology
Systems Science
Cognition
Mathematical and Statistical Techniques
0202 electrical engineering, electronic engineering, information engineering
Cluster Analysis
Power Distribution
Psychology
Cell Cycle and Cell Division
lcsh:Science
Multidisciplinary
Complex Systems
Grid
Cell Processes
Sensor node
Physical Sciences
Engineering and Technology
020201 artificial intelligence & image processing
Wireless Technology
Network Analysis
Statistics (Mathematics)
Research Article
Optimization
Computer and Information Sciences
Decision Making
Network topology
Research and Analysis Methods
Computer Communication Networks
Mobile wireless sensor network
Cluster (physics)
Statistical Methods
lcsh:R
Cognitive Psychology
Biology and Life Sciences
020206 networking & telecommunications
Cell Biology
Signaling Networks
Energy and Power
Key distribution in wireless sensor networks
Cognitive Science
lcsh:Q
Wireless Sensor Networks
Wireless sensor network
Mathematics
Neuroscience
Forecasting
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 12
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....4910b4f20634f82e2cb07cd600e13152