Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach
Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2016/5063261 |
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| author | E. Golden Julie S. Tamil Selvi |
| author_facet | E. Golden Julie S. Tamil Selvi |
| author_sort | E. Golden Julie |
| collection | DOAJ |
| description | Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes. |
| format | Article |
| id | doaj-art-2ccd2dfc63174a1b8b1ce79fa89b92a1 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-2ccd2dfc63174a1b8b1ce79fa89b92a12025-02-03T01:31:25ZengWileyThe Scientific World Journal2356-61401537-744X2016-01-01201610.1155/2016/50632615063261Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy ApproachE. Golden Julie0S. Tamil Selvi1Department of Computer Science and Engineering, Regional Office, Anna University, Tirunelveli, Tamil Nadu 627 007, IndiaDepartment of Electronics and Communication Engineering, National Engineering College, Kovilpatti, Tamil Nadu 628 503, IndiaWireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.http://dx.doi.org/10.1155/2016/5063261 |
| spellingShingle | E. Golden Julie S. Tamil Selvi Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach The Scientific World Journal |
| title | Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach |
| title_full | Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach |
| title_fullStr | Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach |
| title_full_unstemmed | Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach |
| title_short | Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach |
| title_sort | development of energy efficient clustering protocol in wireless sensor network using neuro fuzzy approach |
| url | http://dx.doi.org/10.1155/2016/5063261 |
| work_keys_str_mv | AT egoldenjulie developmentofenergyefficientclusteringprotocolinwirelesssensornetworkusingneurofuzzyapproach AT stamilselvi developmentofenergyefficientclusteringprotocolinwirelesssensornetworkusingneurofuzzyapproach |