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In designing the wireless sensor networks, the energy is the most important consideration because the lifetime of the sensor node is limited by the battery of it. To overcome this demerit many research have been done. The clustering is the one of the representative approaches. In the clustering, the cluster heads gather data from nodes, aggregate it and send the information to the base station. In this way, the sensor nodes can reduce communication overheads that may be generated if each sensor node reports sensed data to the base station independently. LEACH is one of the most famous clustering mechanisms. It elects a cluster head based on probability model. This approach may reduce the network lifetime because LEACH does not consider the distribution of sensor nodes and the energy remains of each node. However, using the location and the energy information in the clustering can generate big overheads. In this paper we introduce CHEF - cluster head election mechanism using fuzzy logic. By using fuzzy logic, collecting and calculating overheads can be reduced and finally the lifetime of the sensor networks can be prolonged. To prove efficiency of CHEF, we simulated CHEF compared with LEACH using the matlab. Our simulation results show that CHEF is about 22.7% more efficient than LEACH.
Kim et al. (Fri,) studied this question.