Towards energy-efficient IoT routing: A hybrid optimization and DL approach

Abstract

While the energy levels of nodes in these networks vary, there is still a need for further advancements to fully optimize the performance of heterogeneous Wireless Sensor Networks (WSNs). Efficient data routing plays a vital role in improving the IoT-enabled WSNs overall performance. Existing routing protocols face difficulties in addressing issues like frequent node movement, optimizing energy efficiency, scalability, and adapting to changing network conditions. These challenges need to be addressed to ensure effective routing in IoT-based heterogeneous WSNs. Thus, a new approach for optimal routing in IoT-based heterogeneous WSNs that utilizes the STGOA is proposed. In the Network Modeling stage, various components of the IoT-enabled heterogeneous WSN, including sensor nodes, servers, the internet, BS, and the network topology, are defined. The interactions between these elements are established to define the communication structure and flow within the network. The Optimal Routing stage begins with the clustering of sensor nodes via the Fuzzy C Means (FCM) method. After clustering, the STGOA approach is employed to choose the optimal paths while considering critical constraints like energy consumption, trust, distance, security, and delay. The proposed STGOA method achieved maximum energy rate of 0.368 J at node 100 and 0.375 J at node 200 as compared to the other methods like GWO, SHO, GOA, STO, BOA, NBO, JFO, EEMCM and GMPSO.