Cluster formation and optimal cluster head selection are two optimization problems in wireless sensor network (WSN) for prolonged lifetime. To address the above mentioned issue, biogeography based selection of cluster heads along with efficient cluster formation is propound in this article which improves the performance of fuzzy based enhanced clustering scheme (FBECS). A novel fitness function is formulated by making use of remnant energy, distance to base station (BS), and density around node for optimal cluster head selection using biogeography based optimization (BBO). A rank based mechanism is developed for non‐cluster head nodes for selecting their cluster head. Routing technique for region based forwarding is designed to improve the lifetime expectancy. The proposed I‐FBECS is compared with two state of the art protocols namely LEACH and FBECS. Simulation results reveal an improved stability period by 33.8% and 38.9% over FBECS and LEACH, respectively. The proposed I‐FBECS exhibits better load balancing and improvement in terms of more alive nodes per round, more packets forwarded to the BS, improved average remnant energy, and extended lifetime. The proposed I‐FBECS is suitable for applications where the BS is located at a distant place.
With huge advancements in Microelectronics, Wireless Sensor Network (WSN) is conquering its domain with low powered tiny sensors. These sensors are commonly used in monitoring and surveillance of remote and urban areas. Since the power supply to these tiny sensors is a battery, for the maximal efficiency of WSN, there arises a need for a maximal lifetime of these tiny sensors wherever they are deployed. Clustering is a promising solution but there is uncertainty in the selection of cluster heads. Fuzzy logic, however, can contribute to the selection of optimal candidates to play the role of such cluster heads. To muddle through the issue, we have proposed a fuzzy-based energy-efficient clustering approach (FEECA) in wireless sensor networks and also designed a fuzzy inference system that defines influential parameters for selecting optimal candidates for cluster head(CH) role. To reduce the expenditure borne by communication, master nodes are selected among the chosen cluster heads so that their communication distance to the sink can be reduced. In the proposed scenario the area is divided into the diagonal form to reduce the load of the network. Each part consists of a Sensor Node (SN), cluster head, and master node. In the diagonal form, the network is divided so that the distance travelled by the data packet through the diagonal path is always smaller than the distance in which the horizontal path exists, based on the triangular inequality theorem. Simulation experiments were conducted and experimental results unveiled better performance of proposed work in terms of stability period, more packet delivery to sink and extended lifetime.
The uttermost requirement of the wireless sensor network is prolonged lifetime. Unequal energy degeneration in clustered sensor nodes lead to the premature death of sensor nodes resulting in a lessened lifetime. Most of the proposed protocols primarily choose cluster head on the basis of a random number, which is somewhat discriminating as some nodes which are eligible candidates for cluster head role may be skipped because of this randomness. To rule out this issue, we propose a deterministic novel energy efficient fuzzy logic based clustering protocol (NEEF) which considers primary and secondary factors in fuzzy logic system while selecting cluster heads. After selection of cluster heads, non-cluster head nodes use fuzzy logic for prudent selection of their cluster head for cluster formation. NEEF is simulated and compared with two recent state of the art protocols, namely SCHFTL and DFCR under two scenarios. Simulation results unveil better performance by balancing the load and improvement in terms of stability period, packets forwarded to the base station, improved average energy and extended lifetime.
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