This abstract provides a novel strategy for tackling optimization problems in clustering techniques through the development of creative and resource-saving cluster-based routing protocols using advanced computing techniques. In many fields, such as wireless sensor networks, data mining, and picture segmentation, clustering is a crucial approach. However, the efficiency of traditional clustering techniques is frequently hampered by optimization issues. This study promotes the use of intelligent computing methods into the creation of cluster-based routing protocols as a means of overcoming these difficulties. The proposed protocols attempt to improve the overall performance of clustering processes by using the power of artificial intelligence, machine learning, and other cutting-edge computational techniques.

The development of energy-efficient techniques for cluster-based routing protocols is a major area of research. In contexts with limited resources, such wireless sensor networks, where energy-efficient communication directly affects the network's operational lifetime, energy consumption is a major concern. By carefully controlling data transmission, reception, and node activation inside clusters, the protocols seek to maximize energy efficiency. The protocols are also made to change dynamically with the state of the network. Traditional clustering techniques sometimes rely on static settings, which might not be able to adequately handle changing conditions. The proposed protocols can assess real-time data, forecast changes, and modify cluster formations and routing schemes accordingly thanks to the integration of intelligent computing.

The two expected advantages of this research are as follows: First, the novel protocols promise to resolve common optimization issues with conventional clustering approaches. Second, it is anticipated that putting a focus on energy efficiency will greatly increase the lifespan of networks with limited resources. This study adds to the growing body of information relating to intelligent computing, energy-efficient networking, and clustering. This abstract summarizes a project that aims to revolutionize clustering approaches by using intelligent computing techniques. The suggested cluster-based routing protocols aim to improve the performance and endurance of various types of networks by addressing optimization difficulties and prioritizing energy efficiency.