A Polling-Based Transmission Scheme Using a Network Traffic Uniformity Metric for Industrial IoT Applications

Author:

Igarashi YuichiORCID,Nakano Ryo,Wakamiya NaokiORCID

Abstract

The Industrial Internet of Things (IIoT) applications are required to provide precise measurement functions as feedback for controlling devices. The applications traditionally use polling-based communication protocols. However, in polling-based communication over current industrial wireless network protocols such as ISA100.11a, WirelessHART have difficulty in realizing both scheduled periodic data collection at high success ratio and unpredictable on-demand communications with short latency. In this paper, a polling-based transmission scheme using a network traffic uniformity metric is proposed for IIoT applications. In the proposed scheme, a center node controls the transmission timing of all polling-based communication in accordance with a schedule that is determined by a Genetic Algorithm. Communication of both periodic and unpredictable on-demand data collection are uniformly assigned to solve the above difficulties in the schedule. Simulation results show that network traffic is generated uniformly and a center node can collect periodic data from nodes at high success ratio. The average success probability of periodical data collection is 97.4 % and the lowest probability is 95.2 % .

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference30 articles.

1. The Internet of Things

2. The Internet of Things

3. From Machine-to-Machine to Internet of Things: Introduction to a New Age of Intelligence;Holler,2014

4. Secure Communication and Data Processing Challenges in the Industrial Internet;Andrei;Baltic J. Mod. Comput.,2016

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