TSTSS: A Time-Sensitive Task Scheduling System for Multi-modal Industrial Internet of Things

Abstract

We propose a task scheduling system for Multi-modal Industrial Internet of Things (IIoT). The system is based on the improvement of Kubernetes and the parsing of task. Furthermore, it can dynamically select the appropriate nodes to parallelly process sub-tasks according to theirs latency requirement and real-time communication and computing conditions. It can effectively solve the impact of latency sensitivity differences on task scheduling in IIoT.

Fan DANG

Research Assistant Professor

My research interests include industrial intelligence and edge computing.