Optimization of Flow Allocation in Asynchronous Deterministic 5G Transport Networks by Leveraging Data Analytics

Prados-Garzon, Jonathan; Taleb, Tarik; Bagaa, Miloud

doi:10.1109/tmc.2021.3099979

Cited by 19 publications

(15 citation statements)

References 36 publications

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“…e performance of time synchronization depends on the precise clock source provided by the master clock [14][15][16][17][18].…”

Section: All-domain Fusion Based Time Synchronization Protocol (Af-tsp)mentioning

confidence: 99%

“…Similarly, there is an inevitable and urgent need for timesensitive network services in many industries, such as medical care, augmented reality and virtual reality (AR/VR), and self-driving vehicles [11][12][13][14][15]. Among all solutions, time synchronization is the key prerequisite, and so is the ATSN [16,17]. Time synchronization facilitates network nodes to transmit information while maintaining accurate time.…”

Section: Introductionmentioning

confidence: 99%

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All-Domain Fusion-Based Time Synchronization Protocol in SD-ATSN

Zhu

Chen²,

Chen

et al. 2022

Mobile Information Systems

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As combat scales up and weapons become more intelligent, airborne networks (AN) must facilitate high-precision communications. This means that the airborne network should have communication capability with minimum delay, low jitter, and high reliability, and this new type of AN is called an airborne time-sensitive network (ATSN). A prerequisite to guarantee the above communication capability is to have a high precision time synchronization protocol. To plug this gap, we have designed a software-defined airborne time-sensitive network (SD-ATSN) architecture based on the benefits of software-defined centralization and flexibility. It supports our proposed all-domain fusion-based time synchronization protocol (AF-TSP) to support precise time synchronization between ATSN platforms. In AF-TSP, we innovatively propose an all-domain (land, sea, air, and space) master clock hot standby mechanism to cope with the existing instability and poor robustness in AN. In the key problem of the master clock election, we first completed a rough election utilizing improved K-Means++. Subsequently, on top of the rough election, we inserted a mixed mutation operator to improve the convergence of the multiobjective optimization algorithm No Dominant Sorting Genetic Algorithm-II (NSGA-II). The control delay, clock accuracy, and path reliability coefficient are the optimization objectives for selecting the appropriate master clock. Simulation results demonstrate that our protocol has advantages in terms of synchronization precision, communication delay, and network robustness.

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“…e performance of time synchronization depends on the precise clock source provided by the master clock [14][15][16][17][18].…”

Section: All-domain Fusion Based Time Synchronization Protocol (Af-tsp)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

All-Domain Fusion-Based Time Synchronization Protocol in SD-ATSN

Zhu

Chen²,

Chen

et al. 2022

Mobile Information Systems

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“…Some works have proposed analytical E2E delay models for virtualized wireless networks and network slices [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Although there are also works providing performance models for a specific network domain (e.g., RAN, TN, and CN) [ 28 , 29 , 30 , 31 ] or component (e.g., gNB and UPF) [ 32 , 33 ], here we will only review E2E delay models, i.e., those considering every network domain. Analytical models are crucial to assist autonomous solutions for the management and operation of the network and to perform offline network performance assessments and optimization.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Then, all types of traffic receive the same treatment. This technology is affordable and easy to configure, but it is hard to support deterministic QoS in these networks [ 30 ]. What is more, the computation of the E2E worst-case delay is an nondeterministic polynomial time (NP)-hard problem [ 61 ].…”

Section: System Modelmentioning

confidence: 99%

“…What is more, the computation of the E2E worst-case delay is an nondeterministic polynomial time (NP)-hard problem [ 61 ]. On the other hand, asynchronous TSN is more complex to configure [ 62 , 63 ], but provides deterministic QoS through per-link traffic regulation and traffic prioritization [ 30 ]. Asynchronous TSN is suitable to serve non-periodic deterministic traffic patterns and enables its coexistence with the best effort one [ 64 ].…”

Section: System Modelmentioning

confidence: 99%

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5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0

Chinchilla-Romero

Prados-Garzon

Ameigeiras

et al. 2021

Sensors

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Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among PLs in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the E2E mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of TSN against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

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