Kablosuz sensör ağları için bulanık mantık tabanlı kümeleme optimizasyonu

Clustering is a powerful technique that organizes the process of the system to confirm network scalability, reduces the consumed energy, as well as realizes the network lifetime extension. The clustering routing algorithm is commonly utilized within wireless sensor networks (WSNs) due to its high-energy efficiency and scalability. The energy source in WSNs may be restricted to the battery's ability of the sensor nodes. As transmission energy is proportional to the distance that exists separating a sender to receiver, clustering in WSN can assist reduce energy usage. Data may be sent from any sensor node to corresponding Cluster Head (CH) for efficient information gathering. There is a need for maximizing the WSNs lifetime, optimization of network operation is crucial. The suggesting clustering algorithm is applied to enhance the lifetime of WSNs by selecting cluster heads (CHs) and forming clusters. Researchers have developed Fuzzy Logic (FL) to address the issue of overburdening Cluster Head (CH) during cluster formation in WSN. FL focuses on the CH efficiency, distributing load between sensor nodes for enhancing lifetime of network. The proposed protocol fuzzy logic based-clustering (FLB-CLS) outperforms FD-LEACH and OC-FCM, regarding network lifetime and throughput, also improving advance for networks that have higher node density. Each sensor node calculates the probability of CH using a distributed fuzzy inference system. For various network sizes and topologies, the results of simulation specify enhancements in energy efficiency as a result of network lifetime along with consumed energy balancing across sensor nodes. with concerning to first node dead along with total node dead, results demonstrate an average improvement.