Industrial Communication Systems and Their Future Challenges: Next-Generation Ethernet, IIoT, and 5G

Vitturi, Stefano; Zunino, Claudio; Sauter, Thilo

doi:10.1109/jproc.2019.2913443

Cited by 263 publications

(105 citation statements)

References 160 publications

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“…Real-time industrial networks have been extensively addressed by the scientific literature [ 1 , 24 ]. They are communication systems that are specifically designed to effectively interconnect industrial devices, such as controllers, sensors, and actuators.…”

Section: Background: Real–time Industrial Networkmentioning

confidence: 99%

“…In a final session of tests, we carried out a set of simulations to investigate the impact of the execution times on the minimum cycle time (MCT), a typical performance index for industrial networks [ 1 , 39 ]. The MCT has been introduced for networks based on a cycle (that are widespread in the industrial scenario) in which a master device regularly polls a set of slaves.…”

Section: Performance Assessmentmentioning

confidence: 99%

“…Modern factory automation systems are based on distributed architectures in which communication networks are exploited to connect industrial controllers and field devices, like sensors and actuators, located throughout a plant, possibly at considerable distances [ 1 ]. During operation, the components of these systems execute tasks (e.g.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems

Fedullo

Tramarin

Vitturi

2020

Sensors

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Factory automation systems based on the IEEE 802.11 Wi-Fi standard may benefit from its Multi-Rate Support (MRS) feature, which allows for dynamically selecting the most suitable transmission rate for the targeted application context. The MRS is implemented by means of rate adaptation algorithms (RAAs), which has already demonstrated to be effective to improve both timeliness and reliability, which are typically strict requirements of industrial real-time communication systems. Indeed, some of such algorithms have been specifically conceived for reliable real-time communications. However, the computational complexity of such algorithms has not been effectively investigated yet. In this paper, we address such an issue, particularly focusing on the execution times of some specific rate adaptation algorithms, as well as on their impact on the automation tasks. In this respect, after a formal description of the algorithms, we present the outcomes of an extensive experimental session, which includes practical measurements and realistic simulations. The obtained results are encouraging, since the measured execution times indicate that rate adaptation algorithms can be profitably adopted by industrial automation systems, allowing for improving their reliability and timeliness without impacting on the overall performance.

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Section: Background: Real–time Industrial Networkmentioning

confidence: 99%

Section: Performance Assessmentmentioning

confidence: 99%

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The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems

Fedullo

Tramarin

Vitturi

2020

Sensors

Self Cite

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“…This paper deals with the problem of creating spatial position sensors (near spatial navigation) in the concepts: Industry 4.0 (Industry 4.0), Industrial Internet of Things (IIoT), Virtual (VR -Virtual Reality) and augmented (AR -Augmented) Reality) Reality, the 5th generation of mobile networks (5G -5 Generation of Digital cellular networks) [1]. In addition to optical ambient recognition devices and inertial sensors, MT -Magnetic Tracking [2] are considered effective sensors.…”

Section: Formulation Of the Problemmentioning

confidence: 99%

Signal Model for Spatial Position Sensors in Magnetic Tracking Systems

Holyaka

Marusenkova

Fedasyuk

2020

Innovative Technologies and Scientific Solutions for Industries

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The subject of research is the process of forming signals in magnetic tracking systems including those used for spatial position calculation within the concepts of Industry 4.0 and Industrial Internet of Things. Such systems are based on calculating the spatial position of objects upon measurements of reference magnetic fields in low-frequency electromagnetic radiation spectrum. The goal is to develop and verify a signal model for spatial position calculating in magnetic tracking systems. The signal model is developed upon experimentally obtained dependencies of the informative signals on the distances and angles between sensor and actuator coils. Objectives: analysis of signals in magnetic tracking systems, development of tools for experimental study, mathematical interpretation of the research results along with development of the signal model, verification and use of the developed model. General scientific methods were used, including experiment, measurement, analysis, synthesis, probabilistic and statistical methods. We have obtained the following results: The structure of a signal chain of the programmable magnetic tracking systems and its implementation on the basis of PSoC of 5LP Family by Cypress Semiconductor has been disclosed. Experimental results obtained at different distances and angles between the actuator and sensor coils have been presented. For spatial positions calculation signal models that describe distribution of magnetic fields and signals of sensor coils are used. We have analyzed typical inaccuracies and ways of their minimization. For verification of the introduced signal model we propose to use the mean square deviation of normalized signals. Conclusions. A signal model for the mutual position of actuators and sensors in magnetic tracking systems has been developed. The model describes functional dependencies whose main parameters are the distances and angles between coils. Further development of the presented results implies the proposed signal model to be used when solving problems of developing and specifying algorithms of spatial position calculation, system debugging and rapid analysis, optimization of calibration procedures.

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“…IPAS are based on a five-level hierarchy [11]. The sensor and actuator level consist of field devices that communicate over a wireless network with a Gateway that bridge to the control level.…”

Section: A Industrial Process Automation Systems (Ipas)mentioning

confidence: 99%

Industry 4.0: Smart Contract-based Industrial Internet of Things Process Management

Garrocho¹,

Ferreira

Júnior³

et al. 2019

Anais Estendidos Do IX Simpósio Brasileiro De Engenharia De Sistemas Computacionais (SBESC Estendido 2019)

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Through the Industrial Internet of Things (IIoT), a smart factory has entered the boom period expecting significant investments. In this new environment, Machine-to-Machine (M2M) communication has shown immediate potential in IIoT applications. However, most M2M communication implementations use the centralized model in which it requires a reliable intermediary for transactions between machines. Using smart contracts in M2M communication would allow a decentralized network to be used without the need for a trusted intermediary. In order to provide security, privacy, and decentralization in M2M communication and IIoT processes, a middleware based on a smart contract is proposed. Such a proposal is analyzed at the industrial level and evaluated for impacts against the stringent communication requirements that industrial applications require. Experimental results show that the application of smart contracts offers greater security and privacy than traditional proposals, but time requirements of real-time systems must still be optimized for smart contracts to be applied at the industrial field.

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Industrial Communication Systems and Their Future Challenges: Next-Generation Ethernet, IIoT, and 5G

Cited by 263 publications

References 160 publications

The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems

The Impact of Rate Adaptation Algorithms on Wi-Fi-Based Factory Automation Systems

Signal Model for Spatial Position Sensors in Magnetic Tracking Systems

Industry 4.0: Smart Contract-based Industrial Internet of Things Process Management

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