Exploiting redundancy and path diversity for railway signalling resiliency

López, Igor Filibi; Aguado, Marina; Ugarte, Denis; Mendiola, Alaitz; Higuero, Marivi

doi:10.1109/icirt.2016.7588765

Cited by 8 publications

(8 citation statements)

References 22 publications

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“…For MPTCP, network layer information can be utilized mainly in subflow management and subflow routing, subflow management includes the evaluation and control of existing subflows, and subflow routing determines the route of each subflow, they all contribute to the performance enhancement of MPTCP. In order to get the connection with the network layer, the cross layer optimization for MPTCP is often combined with network layer techniques such as SDN [13], [14], [21], MPLS (multi-protocol label switching) [22], [23], LIPS (locator/identifier separation protocol) [24], [25], or source routing [26]. To fully utilize network resources for MPTCP, researches have been studied in different aspects.…”

Section: B Cross Layer Optimization For Mptcpmentioning

confidence: 99%

GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing

Zhu

Chen

et al. 2020

IEEE Access

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Multipath TCP has attracted increasing attention as a promising technology for 5G networks. To fully utilize network interfaces on multi-homed terminals and the whole network resources, MPTCP is proposed as an extension of TCP to transfer packets concurrently over multiple paths. Cross layer optimization techniques have been applied for MPTCP such as routing and path management. However, existing multipath routing algorithms and network modeling techniques are facing the challenges of subflow asymmetry due to network heterogeneity, thus cannot handle routing optimization problems comprehensively. To address these problems, in this paper, firstly, a novel Graph Neural Network (GNN) based multipath routing model is proposed to explore the complications among links, paths, subflows and the MPTCP connection on various topologies. Leveraging the GNN model, expected throughput can be predicted with given network topology and multipath routes, which can further be the guidance for optimzing the multipath routing. Then, GCLR, a GNN based cross layer optimization system for MPTCP by routing, is proposed with the help of SDN (Software Defined Networking). According to simulation results, our off-line learned GNN model can predict the expected throughput of specific MPTCP connections with very low error. Besides, it's validated that the model has high generalization ability in terms of connection arbitrary and topology arbitrary, it can maintain MSE (mean squared error) at a low level when the situations are not seen during training, which is sufficient for throughput prediction in multipath routing decisions. Finally, the online routing optimization system is realized using SDN, experimental results show that our proposed routing optimization system can achieve significant throughput enhancement compared with traditional multipath routing algorithms. INDEX TERMS Routing, multipath TCP, graph neural network, cross layer optimization, software defined networking.

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Section: B Cross Layer Optimization For Mptcpmentioning

confidence: 99%

GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing

Zhu

Chen

et al. 2020

IEEE Access

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“…However, MPTCP only guarantees the E2E redundancy and does not take care about path diversity. In [5], an MPTCP extension, which merges spatial and temporal redundancy, is proposed combined with MPLS in order to assure the required E2E path diversity and avoid correlated communication errors. However, the distributed control of MPLS does not provide enough flexibility to dynamically modify routes and reconfigure the network in case of failure.…”

Section: Related Workmentioning

confidence: 99%

“…To summarize, with the purpose of achieving the reliability of legacy dedicated circuits, and complying with the aforementioned constrains, it is crucial to use resilient architectures that apply spatial and temporal redundancy techniques [5]. However, redundancy without path diversity does not provide the needed resiliency for facing correlated communication errors.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptable Train-to-Ground Communication Architecture Based on the 5G Technological Enabler SDN

2019

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Railway communications are closely impacted by the evolution and availability of new wireless communication technologies. Traditionally, the critical nature of railway services, the long lifecycle of rolling stock, and their certification processes challenge the adoption of the latest communication technologies. A current railway telecom trend to solve this problem is to design a flexible and adaptable communication architecture that enables the detachment of the railway services—at the application layer—and the access technologies underneath, such as 5G and beyond. One of the enablers of this detachment approach is software-defined networking (SDN)—included in 5G architecture—due to its ability to programmatically and dynamically control the network behavior via open interfaces and abstract lower-level functionalities. In this paper, we design a novel railway train-to-ground (T2G) communication architecture based on the 5G technological enabler SDN and on the transport-level redundancy technique multipath TCP (MPTCP). The goal is to provide an adaptable and multitechnology communication service while enhancing the network performance of current systems. MPTCP offers end-to-end (E2E) redundancy by the aggregation of multiple access technologies, and SDN introduces path diversity to offer a resilient and reliable communication. We carry out simulation studies to compare the performance of the legacy communication architecture with our novel approach. The results demonstrate a clear improvement in the failover response time while maintaining and even improving the uplink and downlink overall data rates.

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“…Os caminhos compartilhados podem atravessar gargalos, experienciando problemas como o bufferbloat [Felix et al 2017], que limitam os benefícios da redundância. As abordagens multi-camadas, em que os protocolos da camada de rede transmitem os sub-fluxos por caminhos disjuntos, podem prover uma maior diversidade para as transmissões multicaminhos [Lopez et al 2016]. Entretanto, isto pode criar um engessamento indesejável entre os protocolos das camadas adjacentes.…”

Section: Introductionunclassified

Escalonador de Pacotes para Transmissão por Multi-caminhos Não-Correlacionados em Redes Heterogêneas sem Fio

Felix¹,

Steuck²,

Santos³

et al. 2018

Anais Do XXXVI Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC 2018)

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Esforços acadêmicos e industriais buscam melhorar o desempenho das redes heterogêneas sem fio para que ofereçam os requisitos míninos de latência e vazãoás aplicações sensíveis ao atraso, tais como jogos online, e fluxos de voz e vídeo. O Protocolo de Controle de Transmissão Multi-caminhos (MPTCP) foi projetado para atender a essa demanda. Ele provê um escalonador redundante, que replica os pacotes de dados em múltiplos caminhos, para contrabalançar os efeitos negativos da heterogeneidade. Entretanto, gargalos compartilhados entre os caminhos fim-a-fim reduzem os benefícios providos pelo escalonador. Desta forma, este trabalho apresenta RED (REdundant Diversity scheduling), um escalonador que prioriza a replicação dos pacotes por caminhos não-correlacionados. RED replica os pacotes nos caminhos com base no coeficiente de correlação de Spearman. Os resultados demonstram que RED prioriza o uso de caminhos com baixa correlação e reduz a sobrecarga na rede com um menor número de pacotes replicados, além de prover uma melhora significativa no desempenho da transmissão.

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Exploiting redundancy and path diversity for railway signalling resiliency

Cited by 8 publications

References 22 publications

GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing

GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing

An Adaptable Train-to-Ground Communication Architecture Based on the 5G Technological Enabler SDN

Escalonador de Pacotes para Transmissão por Multi-caminhos Não-Correlacionados em Redes Heterogêneas sem Fio

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