Experimental Evaluation of Techniques to Lower Spectrum Consumption in Wi-Red

Cena, Gianluca; Scanzio, Stefano; Valenzano, Adriano

doi:10.1109/twc.2018.2884914

Cited by 9 publications

(4 citation statements)

References 20 publications

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“…On the other hand, these essential activities must be kept as simple as possible, is such a way to be easily accomplished by workers in the industry. Concerning equipment involved in networked systems, both wired (e.g., TSN [6]) and wireless communication technologies are often characterized by tight constraints, including real-time [7], reliability [8], [9], safety [10], security [11], [12], and power consumption [13], [14]. Therefore, proper configuration is demanded to maximize performance.…”

Section: Introductionmentioning

confidence: 99%

QRscript: Embedding a Programming Language in QR codes to support Decision and Management

Scanzio,

Cena,

Valenzano

2024

Preprint

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Section: Introductionmentioning

confidence: 99%

QRscript: Embedding a Programming Language in QR codes to support Decision and Management

Scanzio,

Cena,

Valenzano

2024

Preprint

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“…Traditionally, industrial communications have been centred on the use of specific local network architectures for the interconnection of specialized components and applications, like Programmable Logic Controllers (PLCs), Supervisory Control and Data Acquisition (SCADA) systems and Distributed Control Systems (DCSc); these network architectures have gradually evolved from field buses to industrial Ethernet solutions and, more recently, to Wireless LAN (WLAN) technologies [6]. The latter may need some enhancements to meet the strict requirements of the industrial environment in terms of Quality of Service (QoS) and reliability; see, e.g., [7]- [10].…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, the detection of possible collision courses in real time and the automated machinery control for run-time human collision avoidance would imply the satisfaction of strict latency constraints [13], [14] and extremely high reliability levels. Enhancing reliability in this kind of industrial manufacturing environment has been exactly the goal of the already cited works [7]- [10], by replicating messages over multiple independent channels in the WiFi context, along the line suggested by the Parallel Redundancy Protocol (PRP) specified in the IEC 62439-3 standard (see [15] for the latest edition).…”

Section: Introductionmentioning

confidence: 99%

Increasing safety levels in human-machine interaction by beyond-5G wireless redundancy

Borsatti¹,

Davoli²,

Lombardo³

et al. 2022

ITU J-FET

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Factory automation in the context of Industry 4.0/5.0 requires safety levels to satisfy more stringent and tight limits than those available so far. This goal is further challenged by the extension to the wireless environment of industrial shop floor communications that were traditionally based on cabled networks. Starting with wireless LANs, the trend towards the use of industrial wireless is fostered by the advent of fifth Generation (5G) private connectivity and is bound to increase its pace in the evolution towards 6G. In particular, the interaction of human operators with industrial robots and autonomous vehicles on the shop floor is posing stringent safety requirements that in turn push forward the dependability and reliability limits of wireless connectivity. To help achieve these limits, this paper proposes a dynamic redundancy mechanism based on the real-time activation/deactivation of radio bearers instantiated between mobile devices carried by humans and machines and multiple base stations, to achieve guaranteed upper bounds on packet loss probability in the communication of data related to operational safety control loops. An optimization problem is posed, and suitable heuristics are evaluated by simulation in a 5G and beyond wireless environment, aiming to dynamically maintain the required reliability levels with small computational effort.

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“…They also apply to seamless redundancy, when the same frame is sent on multiple channels at the same time. In particular, deferral techniques [25] could use ML to determine the primary channel on which the first copy of the frame is sent. Transmission of the second copy is deferred for a while to achieve the best trade-off between reliability and resource consumption.…”

mentioning

confidence: 99%

On the Use of Artificial Neural Networks to Predict the Quality of Wi-Fi Links

Colletto,

Scanzio,

Formis

et al. 2023

IEEE Access

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One of the aspects that mainly characterize wireless networks is their apparent unpredictability. Although several attempts were made in the past years to define for them deterministic medium access techniques, for instance by having data exchanges scheduled by an access point, as a matter of fact they remain a partial solution and are unable to ensure the same behavior as wired infrastructures, since interference may also come from devices outside the network, which obey different rules. A possible way to cope with disturbance on air, both internal and external to the network, is to obtain some knowledge about it by analyzing what happened in the recent past. This information, usually expressed in terms of suitable metrics, is then employed to optimize network operation, for example by prioritizing time-sensitive traffic when needed. In the simplest approaches such metrics coincide with statistical indices evaluated on transmission outcomes, like the failure rate. In this paper we analyze a more sophisticated solution that relies on machine learning, and in particular on artificial neural networks, to predict the behavior of a Wi-Fi link in terms of its frame delivery ratio. Results confirm that more accurate predictions than simpler methods (e.g., moving average) are possible, even when training is partially independent from the specific conditions experienced on the different channels.INDEX TERMS Channel quality prediction, wireless networks, dependable wireless communication, IEEE 802.11, artificial neural networks, machine learning. I. INTRODUCTIONWireless networks are progressively replacing cables in a variety of contexts. In application fields like, e.g., home and car entertainment [1], [2], home automation [3], building automation [4], and sensing [5], their adoption to support wire-free communication (and hence, interaction) among humans and machines, in any combination (H2H, M2M, and H2M), is a popular ongoing trend and one of the main enablers of the so-called Internet of Things (IoT) [6].Besides throughput, also the requirements about latency and dependability may sometimes be quite demanding. This is particularly true in contexts like modern industrialThe associate editor coordinating the review of this manuscript and approving it for publication was Wei Feng .

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Experimental Evaluation of Techniques to Lower Spectrum Consumption in Wi-Red

Cited by 9 publications

References 20 publications

QRscript: Embedding a Programming Language in QR codes to support Decision and Management

QRscript: Embedding a Programming Language in QR codes to support Decision and Management

Increasing safety levels in human-machine interaction by beyond-5G wireless redundancy

On the Use of Artificial Neural Networks to Predict the Quality of Wi-Fi Links

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