QuOTE: A Quality of Service Aware Optimized Traffic Engineering Approach for Efficient Flow Management in SDWS-IoT Networks

Abstract

Quality of Service (QoS) is a serious concern in future generation networks such as Software Defined Wireless Sensor based Internet of Things (SDWS-IoT). Optimized Traffic Engineering (TE) approaches can be used to improve QoS in SDWS-IoT. Most of the existing related works offer Inefficient flow management, Higher power consumption, Non-QoS awareness, Low network lifetime, Tedious network management, etc. Considering these issues in existing related solutions, this work proposes a QoS aware optimized TE approach for efficient flow management in SDWS-IoT network, called QuOTE. It collects the network-wide link QoS statistics and computes the optimized path with respect to different network QoS constraints. The proposed solution is implemented using CPLEX Optimization solver, MATLAB, and Python APIs. The results are compared with some state-of-the-art approaches w.r.t. some well-known QoS metrics. QuOTE offers the substantial efficiency of 9.15%, 21.83%, 17.59%, and 11.05% over other approaches for Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), Average Delay (AD), and Average Jitter (AJ) metrics respectively.