Efficient Localized Data Aggregation of IoT Devices and its Application in Agriculture

The Internet of Things (IoT) has a likely future for all technologies that are associated to the life of humans. Any communication between the social environments along with the user contexts will be made through the smart interfaces. The IoT will have to link to different diverse devices found in the Wireless Sensor Network (WSN). Thus, the routing optimization which is energy efficient has become the primary factor in the performance of the network in the IoT. The widely popular routing used in WSN, Multi-hop Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, is found to be energy inefficient. The work will deal with the choice of finding the optimal path in routing through meta heuristic techniques to improve the lifespan of the network and the energy efficiency of the network. There are different techniques of metaheuristics such as Teacher Learning Based Optimization (TLBO) and Particle Swarm Optimization (PSO) were used effectively for finding optimal solutions for problems. In this work, the PSO-based algorithms were used for locating an optimal sink position to their nodes that make the network efficient in terms of energy. The TLBO metaheuristic is population-based and is based on the concept of teaching and the learning procedure observed in a classroom, which is adapted to the routing problem. The results of the experiment prove that the proposed technique was achieved better levels of performance compared to the other methods..