Abstract
Wireless Sensor Networks are consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, one of the most important issues that need to be enhanced in order to improve the life span of the network is energy efficiency. to overcome this demerit many research have been done. The clustering is the one of the representative approaches. In this paper, we introduce a dynamic clustering algorithm using Fuzzy Logic and genetic algorithm. In fact, using fuzzy system design and system optimization by genetic algorithm is presented approach to select the best cluster head in sensor networks. Using random data set has been addressed to evaluate of fuzzy-genetic system presented in this paper and finally, MSE rate or mean error of sending the messages using proposed fuzzy system in comparison with LEACH method is calculated in select the cluster head. The results of evaluations is representative of a reduction the MSE metric in proposed method in comparison with LEACH method for select the cluster head. Reduce of MSE directly is effective on energy consumption and lifetime of wireless sensor network and can cause the reduce energy consumption and increase network lifetime. KEYWORD Wireless sensor networks, fuzzy logic, fuzzy system, genetic algorithm, energy consumption, clustering.
Highlights
With the advent and development of microelectronic technology in the late 70s, the new sensors were considered
Given the mentioned challenge in this study that is how to choose the best cluster heads in the wireless sensor networks, in this study has been addressed to provide a control way based on the use of genetic fuzzy systems
The selecting cluster heads is done by proposed genetic fuzzy system and based on the properties of each node in the moment of forwarding messages that it may help to distribution of cluster heads in form of more balance in sensor networks
Summary
With the advent and development of microelectronic technology in the late 70s, the new sensors were considered. Using microelectronic technology, were produced the low-cost sensors with small dimensions and low weight. New raw materials for fabrication of the sensor is discovered, and subsequently considered the new principles for practical purposes and data collection. The integration of sensor and electronic circuitry of signal anamorphic is created significant opportunities for the majority of applications. Reduce the size and weight of the sensors and increases their susceptibility is the main goal of many research laboratories and different companies. The small size of sensor nodes was sense of smaller their energy productive batteries
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