Even Lower Latency in IIoT: Evaluation of QUIC in Industrial IoT Scenarios

Fernandez, Fatima; Zverev, Mihail; Garrido, Pablo; Juárez, J. R.; Bilbao, Josu; Agüero, Ramón

doi:10.3390/s21175737

Cited by 13 publications

(6 citation statements)

References 29 publications

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“…The experimental results show that QUIC is most beneficial when the user is on a mobile cellular network and also prove that QUIC relies on its congestion control algorithm. Fernández et al [14] analysed the performance of the QUIC protocol as a new transmission alternative for the Internet of Things (IoT) based on the Message Queueing Telemetry Protocol (MQTT) using different network technologies such as WiFi, cellular, and satellite. The results confirm the feasibility of QUIC as an alternative protocol.…”

Section: Related Workmentioning

confidence: 99%

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Cao

et al. 2023

IET Software

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With the vigorous development of mobile Internet and Blockchain, the rapid and secure interaction of high-frequency data in the era of data explosion has gradually become an urgent need for people. Quick User Datagram Protocol Internet Connection Protocol (QUIC) can be perfectly integrated into the Blockchain due to its low latency and high security, providing a safe and reliable transmission service for the Blockchain system. However, QUIC-based distributed Blockchain systems are vulnerable to cyberattacks due to asymmetric encryption and timestamp, which seriously impacts security and fairness. Therefore, based on the self-similarity of QUIC network traffic, this study proposes an anomaly detection model for QUIC network traffic based on Ensemble Empirical Mode Decomposition and Approximate Entropy. The model obtains several intrinsic mode functions and a residual term by decomposing the network traffic, introducing Approximate Entropy to judge the complexity of each component, and using the Hurst parameter to determine the generation of abnormal traffic. Compared with traditional detection methods, the model can effectively overcome the problems of poor adaptive ability and low efficiency and has high accuracy, which can be used for attack detection and prevention of network nodes. K E Y W O R D S computer network security, data flow analysis, software reliability, transport protocols 1 | INTRODUCTION Blockchain technology is an integrated and innovative application of various IT technologies. It is a technical solution for storing, verifying, transmitting, and exchanging network data without relying on a third party and its distributed nodes. It has two core characteristics: data is difficult to tamper with and decentralisation. Based on these two characteristics, the information recorded by the Blockchain is more authentic and reliable, which can help solve the problem of people's mutual distrust [1, 2]. It solves the problem of data trust and security through distributed ledgers, consensus mechanisms, smart contracts, authorisation, and encryption [3]. In recent years, Blockchain technology is continuously empowering various fields. Figure 1 shows a 5G wireless network and Blockchainbased network architecture. The architecture collects real-time data through the Internet of Things and uploads the data and events to the Blockchain platform, enabling secure scheduling of terminal devices connected to the 5G network [4]. Integrating 5G and Blockchain technology will open the era of inter-chain integration, which can provide an efficient, safe, and fast service experience. With the continuous development This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Related Workmentioning

confidence: 99%

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Cao

et al. 2023

IET Software

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“…Simulation in terms of network simulation has already been used many times for validation and testing, e.g., refs. [ 44 , 45 , 46 ]. In [ 47 ], simulation is used for the generation of data sets for machine learning application.…”

Section: State Of the Artmentioning

confidence: 99%

Virtual Commissioning of Distributed Systems in the Industrial Internet of Things

Rosenberger

Selig

Ristić

et al. 2023

Sensors

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With the convergence of information technology (IT) and operational technology (OT) in Industry 4.0, edge computing is increasingly relevant in the context of the Industrial Internet of Things (IIoT). While the use of simulation is already the state of the art in almost every engineering discipline, e.g., dynamic systems, plant engineering, and logistics, it is less common for edge computing. This work discusses different use cases concerning edge computing in IIoT that can profit from the use of OT simulation methods. In addition to enabling machine learning, the focus of this work is on the virtual commissioning of data stream processing systems. To evaluate the proposed approach, an exemplary application of the middleware layer, i.e., a multi-agent reinforcement learning system for intelligent edge resource allocation, is combined with a physical simulation model of an industrial plant. It confirms the feasibility of the proposed use of simulation for virtual commissioning of an industrial edge computing system using Hardware-in-the-Loop. In summary, edge computing in IIoT is highlighted as a new application area for existing simulation methods from the OT perspective. The benefits in IIoT are exemplified by various use cases for the logic or middleware layer using physical simulation of the target environment. The relevance for real-life IIoT systems is confirmed by an experimental evaluation, and limitations are pointed out.

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“…Two of the closest works to ours are those by Fernández et al. [ 45 , 46 ], where the authors assessed the performance of MQTT over QUIC. However, their methodology was different from ours, and they did not foster an evaluation over a real platform.…”

Section: Related Workmentioning

confidence: 99%

“…Other works have exploited similar procedures, such as [ 44 ], where the authors also use , or [ 24 ], where NetEm allows the authors to emulate different channel conditions. In [ 45 , 46 , 53 ], the simulator is used, but the channel is modeled with a point-to-point link, whose configuration parameters are the ones that we have considered in this paper: capacity, delay, and error rate. It is worth mentioning the Pantheon framework [ 54 ], which adopts the Mahimahi [ 55 ] link emulator.…”

Section: Evaluation Testbedmentioning

confidence: 99%

Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices

Jeddou

Fernandez

Díez

et al. 2022

Sensors

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The QUIC protocol, which was originally proposed by Google, has recently gained a remarkable presence. Although it has been shown to outperform TCP over a wide range of scenarios, there exist some doubts on whether it might be an appropriate transport protocol for IoT. In this paper, we specifically tackle this question, by means of an evaluation carried out over a real platform. In particular, we conduct a thorough characterization of the performance of the MQTT protocol, when used over TCP and QUIC. We deploy a real testbed, using commercial off-the-shelf devices, and we analyze two of the most important key performance indicators for IoT: delay and energy consumption. The results evince that QUIC does not only yield a notable decrease in the delay and its variability, over various wireless technologies and channel conditions, but it does not hinder the energy consumption.

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Even Lower Latency in IIoT: Evaluation of QUIC in Industrial IoT Scenarios

Cited by 13 publications

References 29 publications

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Retracted: Anomaly detection with ensemble empirical mode decomposition and approximate entropy for quick user datagram protocol internet connection‐based distributed Blockchain systems

Virtual Commissioning of Distributed Systems in the Industrial Internet of Things

Delay and Energy Consumption of MQTT over QUIC: An Empirical Characterization Using Commercial-Off-The-Shelf Devices

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