An Empirical Survey of Autonomous Scheduling Methods for TSCH

Elsts, Atis; Kim, Seohyang; Kim, Hyung-Sin; Kim, Chong-kwon

doi:10.1109/access.2020.2980119

Cited by 42 publications

(38 citation statements)

References 26 publications

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“…The main drawback of distributed scheduling is the overhead due to 6P transactions. To avoid this overhead, autonomous scheduling [18] was introduced, where nodes allocate cells autonomously (i.e., without negotiation), using a hash function applied to nodes' addresses. More specifically, Orchestra [12] leverages a node-based approach that can follow two different allocation styles, namely, receiver-based and sender-based.…”

Section: A Classification and Related Workmentioning

confidence: 99%

“…ALICE (Autonomous Linkbased Cell Scheduling) [13] replaces the node-based allocation scheme used in Orchestra with a link-based scheme, where each node allocates a cell per slotframe for each unidirectional link. By allocating more cells per slotframe than Orchestra, ALICE exhibits better performance, in terms of packet delivery ratio and latency in almost all scenarios [18].…”

Section: A Classification and Related Workmentioning

confidence: 99%

“…This reduces the negative effects of collisions. Indeed, it was shown in [18] that the cell reallocation improves the performance with respect to the worst-case behavior, while its impact on the average performance is negligible.…”

Section: B Alicementioning

confidence: 99%

“…Many autonomous and distributed SFs have been proposed and evaluated in the literature. However, in almost all previous papers, SFs taking a similar approach are compared (e.g., distribute [17], or autonomous [13], [14], [18]). A thorough performance evaluation that compare SFs taking different approaches (e.g., autonomous, distributed and, possibly, hybrid), and investigate the pros and cons of the considered approaches in different application scenarios is still missing.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Distributed and Autonomous Scheduling Functions for 6TiSCH Networks

et al. 2020

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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. INDEX TERMS Industrial Internet of Things, 6TiSCH Architecture, Scheduling Function, Simulation and Measurements.

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Section: A Classification and Related Workmentioning

confidence: 99%

Section: A Classification and Related Workmentioning

confidence: 99%

Section: B Alicementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of Distributed and Autonomous Scheduling Functions for 6TiSCH Networks

et al. 2020

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“…This scheduler adds three slotframes: one for node-specific unicast cells, one for sending and receiving Enhanced Beacon messages, and one called “common default”, shared by all nodes in the network and used for broadcast messages, such as RPL DIO messages. See Duquennoy et al [ 11 ] and Elsts et al [ 17 ] for the details.…”

Section: Tsch-sim Overviewmentioning

confidence: 99%

TSCH-Sim: Scaling Up Simulations of TSCH and 6TiSCH Networks

Elsts

2020

Sensors

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TSCH (Time-Slotted Channel Hopping) and 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e) low-power wireless networks are becoming prominent in the industrial Internet of Things (IoT) and other areas where high reliability is needed in conjunction with energy efficiency. Due to the complexity of IoT deployments, network simulations are typically used for pre-deployment design and validation. However, it is currently difficult and time-consuming to simulate large-scale IoT networks with thousands of nodes. This paper proposes TSCH-Sim: a new discrete event simulator for IEEE 802.15.4-2015 TSCH and 6TiSCH networks. The evaluation shows that simulation results obtained with TSCH-Sim show a good match with results from other simulators that are commonly used to investigate TSCH networks. At the same time, TSCH-Sim is faster than these alternatives at least by an order of magnitude, making it more practical to carry out simulations of large networks.

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Modeling and analysis of priority and range‐based‐deterministic and synchronous multichannel extension‐guaranteed time slot allocation in IEEE 802.15.4e medium access control protocol

Asuti

Basarkod

2021

Trans Emerging Tel Tech

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Internet of Things (IoT) enabled technology in the current applications such as smart grids, smart cities, and smart health sectors utilize wireless sensor networks (WSN) to establish stable and reliable communication between the nodes. Moreover, the primary requirement of WSN in IoT applications is to provide low-rate data communication. The IEEE 802.15.4e standard-based medium access control (MAC) protocol is found suitable for low-rate data communication in WSN. The IEEE 802.15.4e standard adopts a deterministic and synchronous multichannel extension (DSME) MAC protocol which employs a multisuperframe structure with multichannel data transmission during the contention free period. However, the guaranteed time slot (GTS) allocation process in DSME employed by the standard may not be suitable for an adaptive traffic network scenario that has a direct impact on the throughput and bandwidth utilization. In this article, we develop a priority and range-based DSME-GTS allocation algorithm based on the priorities of end nodes and range estimation. Furthermore, the proposed algorithm is developed for the two types of network scenarios encountered in a star topology-enabled WSN. In scenario-1, the slots allocation process is carried out based on the priorities of end nodes.Next, in scenario-2, the slots allocation process is carried out based on the range estimation of end nodes. Detailed mathematical modeling of the proposed methodology is provided for the various performance metrics. The model is validated using the MATLAB 2017a programming tool. Simulation results show that the proposed methodology outperforms the existing DSME-GTS approaches in terms of performance metrics such as packet delivery ratio, end-to-end delay, packet loss ratio, throughput, delay, bandwidth utilization, and the energy consumption.

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An Empirical Survey of Autonomous Scheduling Methods for TSCH

Cited by 42 publications

References 26 publications

Analysis of Distributed and Autonomous Scheduling Functions for 6TiSCH Networks

Analysis of Distributed and Autonomous Scheduling Functions for 6TiSCH Networks

TSCH-Sim: Scaling Up Simulations of TSCH and 6TiSCH Networks

Modeling and analysis of priority and range‐based‐deterministic and synchronous multichannel extension‐guaranteed time slot allocation in IEEE 802.15.4e medium access control protocol

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