The high rate of growth of multilevel wireless networks has necessitated a great need of energy efficient communication systems to increase network lifetime and improve performance in general. Clustering has been adopted as one of the best methods of energy saving, routing overhead minimization and enhancement of data delivery. This paper is a proposal of a protocol, Energy-Efficient Clustering of Multilevel Wireless Networks with Dynamic Routing Discovery (EECDRD). The given EECDRD protocol combines smart cluster building and adaptive routing exploration that is adaptive and chooses the best routes according to the residual energy of the nodes, the quality, and cost of links, and the communication cost. In contrast to the traditional routing and clustering techniques, EECDRD expects a multi-criteria decision-making process in the selection of cluster head (CH) and the hierarchical determined data aggregation to redistribute the network load and avoid the early failure of nodes. Dynamic routing discovery algorithm is proposed to find energy-constrained paths thus minimizing the rate of route repairs and enhancing the ratio of packet delivery during mobility and under changing traffic loads. The simulation findings revealed that EECDRD is much better than the current protocols in terms of energy consumption, network life, throughput, and end-to-end delay. The application to the heterogeneous and large-scale wireless sensor and mobile ad-hoc network is more efficient, and the proposed solution is a good approach that is scalable and robust to the next-generation IoT communication system.
K et al. (Sat,) studied this question.