A Distributed Real-time Scheduling System for Industrial Wireless Networks

被引:5
|
作者
Modekurthy, Venkata P. [1 ]
Saifullah, Abusayeed [2 ]
Madria, Sanjay [3 ]
机构
[1] Univ Nevada, 4247 SEB,4505 S Maryland Pkwy, Las Vegas, NV 89154 USA
[2] Wayne State Univ, 5057 Woodward Ave,Suite 14110-2, Detroit, MI 48202 USA
[3] Missouri Univ Sci & Technol, 325A Comp Sci Bldg,500 W 15th St Rolla, Rolla, MO 65409 USA
关键词
WirelessHART; real-time networking; distributed scheduling;
D O I
10.1145/3464429
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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. Distributed! IART 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.
引用
收藏
页数:28
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