A centralized scheduling algorithm for IEEE 802.15.4e TSCH based industrial low power wireless networks

Jin, Yichao; Kulkarni, Parag; Wilcox, John M.; Sooriyabandara, Mahesh

doi:10.1109/wcnc.2016.7565002

Cited by 63 publications

(52 citation statements)

References 7 publications

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“…In almost all previous TSCH scheduling, authors either assume that the impact of link qualities or channel variations on performance are negligible (such as [7][8][9][10][11][12][13][14]), or that the instantaneous and complete channel information is available (such as [15][16][17]), or else the channel is modeled quasi-static (such as [18][19][20]). For example, in [15 and 16], it is assumed that the instantaneous CSI is fully measurable and available, therefore one can use an offline method and calculate the optimal scheduling for a TSCH network by the exact rate of packets to be sent over each link.…”

Section: B Related Workmentioning

confidence: 99%

“…In [11], authors present AMUS, which is a focused and traffic-aware scheduler for real-time industrial applications. In this approach, in order to reduce idle listening, more resources are allocated to weak and vulnerable links related to relay nodes near the sink.…”

Section: B Related Workmentioning

confidence: 99%

“…In channel-aware scheduling, CSI can be available either as non-causal CSI, which contains CSI of the past, present, and future slots, or causal CSI, which contains only CSI of the past and present slots. To the best of our knowledge, there are many studies which present new scheduling methods for TSCH networks without considering the impact of CSI (such as [7][8][9][10][11][12][13][14]). We have seen that in some schemes authors assume that perfect non-causal knowledge of CSI is available for the scheduling process (such as [15][16][17]) and in others prior statistical knowledge of link qualities is utilized in order to improve performance (Such as [18][19][20]).…”

Section: Motivationmentioning

confidence: 99%

“…This value is calculated according to equation (6). Hence, the reward obtained during cycle ߬ is given as (11):…”

Section: ) Cmab-based Formulationmentioning

confidence: 99%

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IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach

2020

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In TSCH, which is a MAC mechanism set of the IEEE 802.15.4e amendment, calculation, construction, and maintenance of the packet transmission schedules are not defined. Moreover, to ensure optimal throughput, most of the existing scheduling methods are based on the assumption that instantaneous and accurate Channel State Information (CSI) is available. However, due to the inevitable errors in the channel estimation process, this assumption cannot be materialized in many practical scenarios. In this paper, we propose two alternative and realistic approaches. In our first approach, we assume that only the statistical knowledge of CSI is available a priori. Armed with this knowledge, the average packet rate on each link is computed and then, using the results, the throughput-optimal schedule for the assignment of (slotframe) cells to links can be formulated as a max-weight bipartite matching problem, which can be solved efficiently using the well-known Hungarian algorithm. In the second approach, we assume that no CSI knowledge (even statistical) is available at the design stage. For this zeroknowledge setting, we introduce a machine learning-based algorithm by formally modeling the scheduling problem in terms of a combinatorial multi-armed bandit (CMAB) process. Our CMAB-based scheme is widely applicable to many real operational environments, thanks to its reduced reliance on design-time knowledge. Simulation results show that the average throughput obtained by the statistical CSIbased method is within the margin of 15% from the theoretical upper bound associated with perfect instantaneous CSI. The aforesaid margin is around 18% for our learning-theoretic solution.Index Terms-IEEE 802.15.4e, TSCH, Scheduling, CSI, CMAB.

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Section: B Related Workmentioning

confidence: 99%

Section: B Related Workmentioning

confidence: 99%

Section: Motivationmentioning

confidence: 99%

“…This value is calculated according to equation (6). Hence, the reward obtained during cycle ߬ is given as (11):…”

Section: ) Cmab-based Formulationmentioning

confidence: 99%

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IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach

2020

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“…In the literature, [6][7][8][9][10] relatively recent slot scheduling algorithms for a TSCH network were proposed; they allocate links according to the level of traffic in a convergecast network and aim to transfer all data to the root device within a single slotframe. However, the traffic level can change according to changes in the network environment, such as the participation of new devices or a change of topology.…”

Section: As Shown Inmentioning

confidence: 99%

A virtual slotframe technique for reliable multi-hop IEEE 802.15.4e time-slotted channel hopping network

Chung

2018

International Journal of Distributed Sensor Networks

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Time-slotted channel hopping is one of the medium access control modes defined in IEEE 802.15.4e. Although timeslotted channel hopping provides high reliability, it cannot be achieved automatically. A time-slotted channel hopping should be configured properly according to the dynamic changes in a network. When new devices participate in the network or the data traffic is increased, link allocation may not be possible due to the fixed slotframe length. The simplest way to acquire additional links is to change the length. However, the conventional method to change this length involves significant overhead and the possibility of link failures. In this article, we evaluate the performance of the conventional IEEE 802.15.4e method and analyze the problems that can occur when changing the slotframe length. To resolve these problems, we propose a virtual slotframe technique that forms a logical slotframe by connecting multiple slotframes. A slot scheduler will then perceive the virtual slotframe as merely a long slotframe. The devices can translate the schedules made for the longer slotframe into real links using the virtual slotframe technique. These features allow the time-slotted channel hopping network to allocate additional slots without reconfiguration. The simulation results show that the proposed technique is a maximum of 18 times and an average of 10 times faster than the conventional method.

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An enhanced MSU‐TSCH scheduling algorithms for industrial wireless sensor networks

Jerbi,

Cheikhrouhou,

Guermazi

et al. 2023

Concurrency and Computation

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SummaryThe reliability and latency requirements of wireless sensor network‐based smart grid communications are met in large part by MAC protocols. Developed by IEEE, time slotted channel hopping (TSCH), a method that is effective, dependable, and predictable. However, the TSCH standard does not enable mobility and does not offer any solution for scheduling, especially in IEEE 802.15.4 TSCH, the most recent generation of extremely dependable and low‐power MAC protocols. Recently, MSU‐TSCH a time‐frequency communication schedule was proposed to provide mobility to TSCH. Despite its distinctive qualities, MSU‐TSCH has the drawback of computing the TSCH schedule at each node independently of its traffic load, which can significantly increase the communication delay. Due to this limitation, MSU‐TSCH is not suitable for some delay‐sensitive smart grid applications. In this article, we provide an improved MSU‐TSCH‐based TSCH protocol, called Mobility‐TSCH, that dynamically adjusts time slot assignments based on traffic volume and latency requirement. Moreover, the protocol Mobility‐TSCH adapts to topology changes and supports mobility. Additionally, it optimizes time slot allocation by prioritizing nodes closest to the sink. The performance and evaluation analysis of Mobility‐TSCH compared to the original MSU‐TSCH, reveal that the communication delay is greatly reduced, decreases the average end‐to‐end latency, the high packet delivery ratio (PDR), Increase the performance of both metrics, parent connectivity ratio (PCR) and convergence time (CT), while maintaining a minimal overhead signaling.

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A centralized scheduling algorithm for IEEE 802.15.4e TSCH based industrial low power wireless networks

Cited by 63 publications

References 7 publications

IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach

IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach

A virtual slotframe technique for reliable multi-hop IEEE 802.15.4e time-slotted channel hopping network

An enhanced MSU‐TSCH scheduling algorithms for industrial wireless sensor networks

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