A PSO Based Optimal Route Selection for Adaptive Data Transmission in Industrial Iot

Abstract

In recent years, industrial internet of things (IIoT) has become an important research topic
among industry and academia. In IIoT there is a huge demand for data exchange among
different smart devices with different delay flows. How- ever, there is a less amount of research
has been carried out in this field. In order to address the limitations of the traditional routing
method, the proposed work proposes an adaptive data transmission method with software
defined network (SDN) and edge computing for IIoT. Based on the data streams with different
latency constraints, the data is classified in to two groups: 1. low prioritized data and 2. high
prioritized data for adaptive data transmission. The proposed work gives a numerical modeling
applicable to perform adaptive transmission optimization with a set of the programmable
module structure and ensure cost- effective route establishment with higher throughput,
goodput and minimum delay constraints. The proposed work utilizes bio inspired swarm
intelligence based data-driven cluster head (CH) selection with energy optimized route
formation to obtain an optimal route. The extensive simulation outcome shows that particle
swarm optimization (PSO) based clustering attain better delay, goodput, throughput and path
difference degree as compared to other conventional methods.