Volume 14, Number 4

An Efficient Machine Learning Optimization Model for Route Establishment Mechanism
in IoT Environment


Kishore Golla and S. PallamSetty, Andhra University, India


Internet of Things (IoT) provides interconnection of various wireless communication devices, which offers both ubiquitous accessibility of devices and in-built intelligence capacity. IoT offers interaction with devices and provides sufficient capability advantages of networking and socialization with consideration of intermediate devices. RPL (Routing Protocol for low-power and Lossy Networks) is an attractive model for effective routing techniques in the wireless medium. The increase in demand for wireless systems in terms of energy, reliability, stability, and scale routing IPv6 over 6L0WPAN is being adopted. This research developed an optimized machine learning model (WOABC) routing protocol for route establishment in IoT networks. The constructed RPL routing protocol incorporates an optimization approach for the identification of the best and worst routes in the network. The proposed WOABC evaluates the routing path for data transmission between nodes through optimization techniques for effective route establishment. The optimization of routes is performed with whale optimization techniques. The developed whale optimization technique is incorporated in machine learning networks. Also, the proposed WOABC utilizes an optimization membership function for the identification of the optimal path in the network. The performance of the proposed WOABC is compared with existing techniques such as RPL and Speed – IoT. The comparative analysis showed that the performance of the proposed WOABC is ~3% increased throughput. The performance of the proposed WOABC is significant compared with the existing RPL routing protocol.


RPL, Optimization, Route establishment, Optimization, Whale Optimization