CFGA : Clustering wireless sensor network using fuzzy logic and genetic algorithm Esmaeil saeedian Islamic Azad University of Mashhad Iran e_saeedian@yahoo.com Mehrdad Jalali Islamic Azad University of Mashhad Iran mehrjalali@gmail.com Mohammad Mahdi Tajari Islamic Azad University of Mashhad Iran mm.tajari@gmail.com Massoud niazi Torshiz Islamic Azad University of Mashhad Iran masood.niazi@gmail.com Ghamarnaz Tadayon Islamic Azad University of Mashhad Iran gh_tadayon@yahoo.com Abstract - Wireless sensor networks have numerous nodes with limited energy which have the ability to monitor around themselves and these nodes are scattered in a limited geographic area. One of the important issues in these networks is increasing the network lifetime. In this study, we introduce an efficient protocol for trade-off between loads and increase in life expectancy of the network, known as CFGA (Clustered wsn using fuzzy logic and genetic algorithm) which uses the single - step method for intracluster communication and multi - step for intercluster communication. At the beginning of each round, each node first checks its fuzzy module, and based on output of the fuzzy module, if the clusterhead capability exists for node, it would be ready ( in each region, number of the best nodes would be ready), then at the base station by using genetic algorithm and the location of clusterheads based on minimum energy consumed, the optimum network nodes are determined. In this study, consumption of energy for nodes which are not capable of becoming clustered is prevented and also only nodes with high capabilities in genetic algorithm take part in order to converge faster to the optimum solution. Keywords- Genetic Algorithm; balance energy; wireless sensor networks; cluster classification;fuzzy logic I. INTRODUCTION In the recent years, technological advances and the telecommunications industry, electrical and electronic micro components, leading to construction of small and relatively inexpensive sensors which relate to each other through wireless communication [1]. The networks that to be known wireless sensor networks, have become to a suitable tool for extracting data from the environment and monitoring environmental events and their applications in household, industrial and military, is increasing day to day [2]. In design and development of wireless sensor networks the main issue is sensors energy source limitation. Because of too many sensors in the network, or lack of access to them, replacement or charging sensors’ batteries are not practical. For this reason providing ways to optimize energy consumption, which ultimately increases the network life time, is of great importance[1]. Research has shown that network nodes organized into groups called clusters, can be more efficient in reducing energy consumption, which leads to increase the network lifetime. The network lifetime is the interval running protocol up to the first dead in Nodes [3]. The LEACH protocol [1] is one of the propounded clustering protocols in sensor networks which are made of two setup phase and steady state phase. In steady state phase data transfer is done in a single hop manner to the sink. In each cluster one node is selected as a cluster head and the rest of node’s clusters are called cluster- member. Data collected from member nodes are processed in cluster head before sending to a base station or sink, and then will be sent to the base station after aggregation of data in the form of a package. Since cluster head’s energy consumption is more than ordinary nodes, after a while their energy will be over. Therefore, in LEACH, using dynamic clustering has been introduced. This means that after each send and receive course operations, in other words after each launch of implementation phase, cluster heads are changed randomly and another node is chosen as cluster head. But random selection of cluster heads may lead to improper distribution in the network. This means that in a part of the network under coverage, two or more adjacent cluster heads are placed close together, whereas in any other region there would not be a cluster head. 978-1-4244-6252-0/11/$26.00 ©2011 IEEE