Latency-Aware Function Placement, Routing, and Scheduling in TSN-based Industrial Networks

Bhattacharjee, Sushmit; Alexandris, Konstantinos; Hansen, Emil Alexander Juul; Pop, Paul; Bauschert, Thomas

doi:10.1109/icc45855.2022.9839028

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…However, many jointly routing research works still rely on computationally intensive algorithms, such as ILP. In [13], a multiobjective MILP formulation was employed to separately solve the placement problem and determine the routing and scheduling of flows based on the MILP solution. In [14], a Mixed-Integer Programming (MIP) approach was proposed to calculate static routing and scheduling configurations for load balancing.…”

Section: Studies On Tas Mechanismmentioning

confidence: 99%

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Joint Scheduling and Routing for End-to-End Deterministic Transmission in TSN

Ja,

Zhang,

Xue

et al. 2024

Preprint

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The time-sensitive networking (TSN) technique has shown its potential to provide deterministic communication guarantees for industrial applications. Specifically, the recently applied cyclic queuing and forwarding (CQF) mechanism in TSN can further provide bounded latency and stable delay jitter for time-triggered (TT) flows with simplified configuration of gate control list (GCL) for TSN switches. However, previous traffic scheduling approaches with the CQF mechanism have overlooked the influence of routing strategies on scheduling optimization. To account for the interaction between the scheduling and routing problems, we propose a two-layer heuristic optimization algorithm, called the Joint Optimization on Offset and Route Selection (JOORS). In this algorithm, the inner layer is responsible for selecting routing decisions, while the outer layer focuses on selecting the time offset.The algorithm establishes the connection between the inner and outer decisions through simulating the flow scheduling process. The goal of the JOORS algorithm is to maximize the scheduling success rate for TT flows in a TSN network based on the CQF mechanism.Extensive simulations demonstrate that the JOORS algorithm can significantly improve the scheduling success rate compared to other algorithms and benchmark schemes.

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Section: Studies On Tas Mechanismmentioning

confidence: 99%

“…Fig 13. Scheduling success rate of 1500 TT flows for JOORS algorithm with different numbers of switches.…”

mentioning

confidence: 99%

Joint Scheduling and Routing for End-to-End Deterministic Transmission in TSN

Ja,

Zhang,

Xue

et al. 2024

Preprint

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show abstract

“…Essentially, the transmission gates are either open or closed according to a time schedule called the Gate Control List (GCL), executed periodically. The synthesis of GCLs, based on various data plane approaches is a well-researched topic [25]- [28]. However, this paper focuses on the control and management of TSN bridges using already generated GCLs.…”

Section: A Ieee 8021 Time Sensitive Networking (Tsn)mentioning

confidence: 99%

CORECONF, NETCONF, and RESTCONF: Benchmarking Network Orchestration in Constrained IIoT Devices

Bhat,

Bhattacharjee,

Gündoğan

et al. 2024

IEEE Internet Things J.

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Industry 4.0 promises to unlock the new capabilities for Industrial Internet of Things (IIoT) by transforming a rigid hierarchical automation pyramid into a flatter networked system. IEEE TSN, chosen as one of the Industry 4.0 pillars on the network level, offers mechanisms for deterministic data exchange and high reliability for such systems. Yet, to ensure a flexible and reliable service, a flat networked system requires a more sophisticated orchestration. Consecutively, such orchestration requires certain memory and CPU capacity from the IIoT devices, and the state-of-the art discusses the three candidate protocols, namely: NETCONF, RESTCONF, and CORECONF. This paper analyzes these protocols with a focus on resource-constrained IIoT devices. To compare the parameters a prototype implementation of CORECONF is developed, and extensively benchmarked against other protocols. Results suggest that CORECONF could be the best candidate in terms of time, power, and memory characteristics.

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“…An advanced earliest window heuristic scheduling algorithm was proposed to satisfy all the constraints of scheduling problems in multi-period, multi-queue, and multi-hop scenarios [21]. Bhattacharjee et al [22] proposed a simulated annealing -based meta-heuristic to solve the joint placement, scheduling, and routing optimization problem.…”

Section: Scheduling Solution Overviewmentioning

confidence: 99%

“…Bhattacharjee et al. [22] proposed a simulated annealing ‐ based meta‐heuristic to solve the joint placement, scheduling, and routing optimization problem.…”

Section: Background and Related Workmentioning

confidence: 99%

Hybrid traffic scheduling in time‐sensitive networking for the support of automotive applications

Nie,

Su,

Zhao

et al. 2023

IET Communications

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Time‐sensitive networking (TSN) is considered one of the most promising solutions to address real‐time scheduling in in‐vehicle network due to its capabilities for providing deterministic service. The TSN working group proposed various traffic shaping mechanisms, while deterministic scheduling of hybrid traffic is still not effectively solved since the traffic requirements are difficult to satisfy by standalone or combined mechanisms with fixed time slot divisions. This article presents a time‐aware multi‐cyclicqueuing and forwarding scheduling model, that integrates the no‐wait enabled time‐aware shaper and multi‐cyclic queuing and forwarding shaping models. Then, a scheduling solution, dubbed “TSN scheduling optimizer” (TSO) is proposed that combines optimization methods and incremental techniques. TSO aims to balance the load to maximize flow schedulability while guaranteeing the service requirements of hybrid traffic. Simulation evaluations through OMNeT++ provide a performance assessment of this proposed scheduling model, which can satisfy multiple types of traffic transmission requirements. Furthermore, TSO is compared with other baseline scheduling solutions, and TSO shows efficacy regarding execution time and schedulability.

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Latency-Aware Function Placement, Routing, and Scheduling in TSN-based Industrial Networks

Cited by 10 publications

References 11 publications

Joint Scheduling and Routing for End-to-End Deterministic Transmission in TSN

Joint Scheduling and Routing for End-to-End Deterministic Transmission in TSN

CORECONF, NETCONF, and RESTCONF: Benchmarking Network Orchestration in Constrained IIoT Devices

Hybrid traffic scheduling in time‐sensitive networking for the support of automotive applications

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