Design and Analysis of an Optimized Scheduling Approach using Decision Making over IoT (TOPSI) for Relay based Routing Protocols

Abstract

This research work focuses on support towards QoS approaches over IoT using computational models based on scheduling schemes to enable service oriented systems. IoT system supports on application of day-to-day physical tasks with virtual objects which inter-connect to create opportunities for integration of world into computer-based systems. The QoS scheduling model TOPSI implements a top-down decision making process over top to bottom interconnected layers using service supportive optimization algorithms based on demandable QoS requirements and applications. TOPSI adopts Markov Decision Process (MDP) at the three layers from transport layer to application layer which identifies the QoS supportive metrics for IoT and maximizes the service quality at network layer. The connection cost over multiple sessions is stochastic in nature as service is supportive based on decision making algorithms. TOPSI uses QoS attributes adopted in traditional QoS mechanisms based on transmission of sensor data and decision making based on sensing ability. TOPSI model defines and measures the QoS metrics of IoT network using adaptive monitoring module at transport layer for the defined service in use. TOPSI shows optimized throughput for variable load in use, sessions and observed delay. TOPSI works on route identification, route binding, update and deletion process based on the validation of adaptive QoS metrics, before the optimal route selection process between source and destination. This research work discusses on the survey and analyzes the performance of TOPSI and RBL schemes. The simulation test beds and scenario mapping are carried out using Cooja network simulator.