Optimized Fuzzy Logic Based Energy-Efficient Geographical Data Routing in Internet of Things
K. Aravind, Praveen Kumar Reddy Maddikunta
Abstract
The Internet of Things (IoT) is being the key strategic enabler for realizing the vision of smart cities by allowing everyday objects to be connected through wireless sensor networks (WSNs). In large-scale WSNs, scalability, versatility, path performance, mobility support, and lower routing protocol overhead are all desirable characteristics. Provided the various regional routing schemes suggested, it mostly relies on positioning, location error, and power consumption. The sensor nodes have high routing overhead and uneven energy consumption, that has a considerable influence on network efficiency and lifespan. In this research work, an energy-efficient geographic (EEG) routing protocol is proposed on the basis of defined 6-fold-objective function. During the EEG routings, the best optimum routes are selected by optimized fuzzy logic, where the membership function is maximized. Here, the optimized routing selection considers distance,energy, overhead, delay, Trust,QoS. For the optimization purpose, Harris hawk’s optimization (HHO) is used in this work. Lastly, the suggested work’s performance is investigated using several metrics in comparison to several traditional techniques.