AN OPPORTUNISTIC ROUTE PREDICTION APPROACH OVER IOT NETWORK FOR REACTIVE QOS SUPPORT AND DIFFERENTIAL SERVICES (ORPI)

The need for an adaptive service based QoS supportive routing is a major challenge in IoT networks. Initial study on IoT node / device supported QoS monitoring approaches suggests on route selection and management process. Traditional routing protocols do not support on design aspects of resource management based on service provisioning. Proposed opportunistic route prediction approach for reactive QoS defines ORPI approach, which predicts optimal route based on resources for service in demand and variable number of users or services being supported. ORPI prefers a kmeans clustering approach to support on route prediction and determine QoS as per service in use. ORPI approach is simulated over a scalable testbed and its performance shows that the proposed approach supports on minimal packet loss and optimal end to end delay.