Impact of Fuzzy Inference System for Improving the Network Lifetime in Wireless Sensor Networks - A Survey

被引：0
|
作者：
Rajaram, V. [1 ]
Srividhya, S. [2 ]
Kumaratharan, N. [3 ]
机构：
[1] Sri Venkateswara Coll Engineeing, Dept Informat Technol, Kancheepuram, Tamil Nadu, India
[2] SRM Inst Sci & Technol, Dept Informat Technol, Kancheepuram, Tamil Nadu, India
[3] Sri Venkateswara Coll Engn, Dept Elect & Commun, Kancheepuram, Tamil Nadu, India
来源：
PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP) | 2018年
关键词：
Sensor networks; energy efficiency; clustering; fuzzy logic;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Several applications related to uncertainty problems are resolved by soft computing techniques such as fuzzy logic, genetic algorithm, PSO, Ant colony optimization, etc. Wireless sensor network applications deal mainly on real time applications. Clustering, routing, load balancing are the three main areas in WSN to reduce the energy consumption and also to enhance the network lifetime. There are several algorithms utilizing fuzzy logic for the above listed subareas to attain efficiency in the network lifetime. Few of those algorithms are analyzed in terms of fuzzy inputs, outputs, changes in rules and inference system types. In this survey paper, various clustering methods along with fuzzy logic concepts are discussed which helps to attain maximum network life time, scalability. Finally, all the parameters involved in fuzzy is compared for all the protocols to get overview of the fuzzy power in WSN.
引用
收藏
页码：933 / 937
页数：5
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