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Enhanced time-slotted channel hopping scheduling with quick setup time for industrial Internet of Things networks

Author

Listed:
  • Kanghoon Choi
  • Sang-Hwa Chung

Abstract

Industrial Internet of Things is a technology that increases productivity by combining the Internet of Things platform with an existing industrial environment. An industrial Internet of Things network requires high reliability, low power usage, and timely exchange of information. The 6TiSCH network, a representative industrial Internet of Things network, consists of an Internet of Things protocol stack (6LowPAN, IPv6, etc.) supporting IPv6 and IEEE 802.15.4e TSCH MAC protocols, which are suitable for an industrial sensor network. The IEEE 802.15.4e standard defines a method of executing a schedule; however, the scheduling method has not been defined. In this article, we propose a quick setup scheduling scheme with minimum control messages. The quick setup scheduling scheme has three algorithms: quick setup scheduling Allocation Processing, quick setup scheduling Deallocation Processing, and quick setup scheduling Optimization Processing. Quick setup scheduling is scheduled to be completed quickly with minimal control messages, and the scheduling setup time is short; shorter setup time allows more data to be transmitted, which is an important factor in an industrial Internet of Things network. Simulation results show that through shorter scheduling setup time, quick setup scheduling collects more data than Decentralized Traffic Aware Scheduling, the representative scheduling algorithm. Also, quick setup scheduling ensures optimal scheduling through an algorithm that minimizes the active slot length.

Suggested Citation

  • Kanghoon Choi & Sang-Hwa Chung, 2017. "Enhanced time-slotted channel hopping scheduling with quick setup time for industrial Internet of Things networks," International Journal of Distributed Sensor Networks, , vol. 13(6), pages 15501477177, June.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:6:p:1550147717713629
    DOI: 10.1177/1550147717713629
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