بهبود بهره‌وري انرژي در پروتكل‌هاي خوشه‌بندي در شبكه‌هاي حسگر بي‌سيم

Wireless Sensor Networks (WSNs) consist of small nodes with limited computational power an‎d energy, widely used in industrial, environmental, an‎d medical applications for data collection an‎d transmission. Energy constraints in these nodes make energy optimization a key challenge. Clustering is one of the most effective techniques for energy management in WSNs, as it reduces communication overhead an‎d energy consumption by grouping nodes into smaller clusters. However, the efficiency of clustering depends on the proper distribution of nodes an‎d the appropriate selec‎tion of cluster heads. Cluster optimization can significantly extend the network lifetime by balancing the load an‎d minimizing unnecessary transmissions. In this study, a two level clustering method is employed to balance the network load. Initially, cluster heads are selec‎ted, an‎d then the Main cluster heads responsible for transmitting data to the Base station are determined. To improve this process, the local density of nodes are calculated using a variable radius an‎d considered in cluster-head selec‎tion to reflect node distribution within the network. Two parameters, the clustering radius an‎d the minimum distance between two cluster heads, are dynamically adjusted based on the number of alive nodes, remaining energy, an‎d network density to ensure a better distribution of cluster heads. Moreover, by limiting the number of members in each cluster, overloading of cluster heads is prevented, resulting in more balanced energy consumption. Nodes without a cluster may become cluster heads when necessary to maintain network coverage. Cluster-head an‎d main cluster_head selec‎tion has been improved through a combined metric consisting of energy, local density, an‎d distance, thereby enhancing network performance. Simulations conducted in MATLAB demonstrate that the proposed method significantly increases both the time of the first node death an‎d the last node death while simultaneously achieving a more balanced energy distribution across the network. This approach effectively reduces energy consumption an‎d improves the overall efficiency of wireless sensor networks.

حسين سعيدي

مهدي مهدوي , محمدرضا حيدرپور