Abstract
The 6TiSCH architecture is expected to play a significant role to enable the Internet of Things paradigm also in industrial environments, where reliability and timeliness are of paramount importance to support critical applications. Many research activities have focused on the Scheduling Function (SF) used for managing the allocation of communication resources in order to guarantee the application requirements. Two different approaches have mainly attracted the interest of researchers, namely distributed and autonomous scheduling. Although many different (both distributed and autonomous) SFs have been proposed and analyzed, a direct comparison of these two approaches is still missing. In this work, we compare some different SFs, using different behaviors in allocating resources, and investigate the pros and cons of using distributed or autonomous scheduling in four different scenarios, by means of both simulations and measurements in a real testbed. Based on our results, we also provide a number of guidelines to select the most appropriate SF, and its configuration parameters, depending on the specific use case.
Recommended Citation
F. Righetti et al., "Analysis of Distributed and Autonomous Scheduling Functions for 6TiSCH Networks," IEEE Access, vol. 8, pp. 158243 - 158262, Institute of Electrical and Electronics Engineers (IEEE), Aug 2020.
The definitive version is available at https://doi.org/10.1109/ACCESS.2020.3020153
Department(s)
Computer Science
Research Center/Lab(s)
Center for High Performance Computing Research
Second Research Center/Lab
Intelligent Systems Center
Keywords and Phrases
6TiSCH architecture; Industrial Internet of Things; scheduling function; simulation and measurements
International Standard Serial Number (ISSN)
2169-3536
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2020 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
28 Aug 2020
Comments
This work was supported in part by the Italian Ministry of Education and Research (MIUR) through the framework of the CrossLab Project (Departments of Excellence).