Volume 9, Issue 10 (October 2022), Pages: 81-93

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 Original Research Paper

 Optimized scheduling method in 6TSCH wireless networks

 Author(s): Ines Hosni ^1, *, Ourida Ben Boubaker ²

 Affiliation(s):

 ¹Department of Information Systems, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia
 ²Department of Computer Sciences, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-3349-5786

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2022.10.011

 Abstract:

IEEE802.15.4e-TSCH is a mode exploited by the Internet of Things. Time Slotted Channel Hopping (TSCH) presents an upgrade to the IEEE 802.15.4 to build a Medium Access Control (MAC) for low power and loss network applications in IoT. This norm defines the concept of TSCH based on channel hopping and reservation of bandwidth to achieve energy efficiency, as well as consistent transmissions. Centralized approaches have been proposed for planning TSCH. They have succeeded in increasing network efficiency and reducing latency, but the scheduling length remains not reduced. However, distributed solutions appear to be more stable in the face of change, without creating a priori assumptions about the topology of the network or the amount of traffic to be transmitted. A distributed scheduling allowing neighboring nodes to decide on a coordination system operated by a minimal scheduling feature is currently proposed by the 6TiSCH working group. This scheduling allows sensor nodes to determine when data is to be sent or received. However, the details of scheduling time intervals are not specified by the TSCH-mode IEEE802.15.4e standard. In this work, we propose a distributed Optimized Minimum Scheduling Function (OMSF) that is based on the 802.15.4e standard TSCH mode. For this purpose, a distributed algorithm is being implemented to predict the scheduling requirements over the next slotframe, focused on the Poisson model and using a cluster tree topology. As a consequence, it will reduce the negotiation operations between the pairs of nodes in each cluster to decide on a schedule. This prediction allowed us to deduce the number of cells needed in the next slotframe. Clustering decreases, the overhead processing costs that produce the prediction model. So, an energy-efficient data collection model focused on clustering and prediction has been proposed. As a result, the energy consumption, traffic load, latency, and queue size in the network, have been reduced.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: 6TSCH scheduling, Minimum scheduling function, IEEE 802.15.4e, Clustering

 Article History: Received 15 January 2022, Received in revised form 6 May 2022, Accepted 30 June 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Hosni I and Boubaker OB (2022). Optimized scheduling method in 6TSCH wireless networks. International Journal of Advanced and Applied Sciences, 9(10): 81-93

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9

 Tables

 Table 1 

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