Proposed GA Algorithm with H-Heed Protocol for Network Optimization using Machine learning in Wireless Sensor Networks
Ayan Das Gupta, K. Sathiyasekar, R. Krishnamoorthy, S. Arun, R. Thiyagarajan, S. Padmapriya
Abstract
Wireless sensor networks generally consist of low energy-consuming devices which are eventually distributed in isolated environments. WSN plays a vital role in the sensors as it uses the wireless medium in frameworks. These WSN are used to gather the data or information in a systematic way by using the interference in an environment. Based on the usage of WSN, the sensing of the data is analyzed using the networking. To increase the network capability and its lifetime, the network optimization of the WSN techniques has to be handled in an efficient way. By reducing the cluster of nodes, it can reduce the energy consumption. In this paper, a proposed genetic (GA) algorithm is used to resolve the issues in characterizing the cluster of nodes during the network optimization. The network feasibility and energy consumption can be reduced using heterogeneous heed and celrp protocol. Due to the heed protocol and celrp, the lifetime of the network gets increased due to the minimal loss. The heed and celrp protocol minimize the threshold range by improving the effectiveness in the network. After evaluating it, the network optimization increased the network capability with the low-cost efficiency.