A Distributed Real-time Scheduling System for Industrial Wireless Networks

Author:

Modekurthy Venkata P.1ORCID,Saifullah Abusayeed2ORCID,Madria Sanjay3

Affiliation:

1. University of Nevada Las Vegas, Las Vegas, NV

2. Wayne State University, Detroit, MI

3. Missouri University of Science and Technology

Abstract

The concept of Industry 4.0 introduces the unification of industrial Internet-of-Things (IoT), cyber physical systems, and data-driven business modeling to improve production efficiency of the factories. To ensure high production efficiency, Industry 4.0 requires industrial IoT to be adaptable, scalable, real-time, and reliable. Recent successful industrial wireless standards such as WirelessHART appeared as a feasible approach for such industrial IoT. For reliable and real-time communication in highly unreliable environments, they adopt a high degree of redundancy. While a high degree of redundancy is crucial to real-time control, it causes a huge waste of energy, bandwidth, and time under a centralized approach and are therefore less suitable for scalability and handling network dynamics. To address these challenges, we propose DistributedHART—a distributed real-time scheduling system for WirelessHART networks. The essence of our approach is to adopt local (node-level) scheduling through a time window allocation among the nodes that allows each node to schedule its transmissions using a real-time scheduling policy locally and online. DistributedHART obviates the need of creating and disseminating a central global schedule in our approach, thereby significantly reducing resource usage and enhancing the scalability. To our knowledge, it is the first distributed real-time multi-channel scheduler for WirelessHART. We have implemented DistributedHART and experimented on a 130-node testbed. Our testbed experiments as well as simulations show at least 85% less energy consumption in DistributedHART compared to existing centralized approach while ensuring similar schedulability.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

Reference47 articles.

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3. Texas Instruments. 2016. CC2420 RF-Transceiver. Retrieved from http://www.ti.com/lit/ds/symlink/cc2420.pdf. Texas Instruments. 2016. CC2420 RF-Transceiver. Retrieved from http://www.ti.com/lit/ds/symlink/cc2420.pdf.

4. Embedded Systems Lab. 2019. Testbed. Retrieved from http://neteye.cs.wayne.edu/. Embedded Systems Lab. 2019. Testbed. Retrieved from http://neteye.cs.wayne.edu/.

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