Analysis of Temporal Robustness in Massive Machine Type Communications

Goswami, Debjani; Dzaferagic, Merim; Šiljak, Harun; Das, Suvra Sekhar; Marchetti, Nicola

doi:10.1109/jiot.2022.3228745

Cited by 2 publications

(3 citation statements)

References 47 publications

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“…In this context, we note that the IoMusT has some characteristics in common and several differences with respect to typical applications of interest for 5G. For example, applications relying on 5G for (massive) machine-type communications (MMTC) [21]- [27] typically focus on dense deployments of machine-type devices, with intermittent or erratic communication patterns. While some IoMusT deployments can be dense, especially if they involve interactions between the performers and their audience [11], IoMusT communication patterns are predictable and periodic for the whole duration of a performance.…”

Section: Introductionmentioning

confidence: 99%

Latency and Reliability Analysis of a 5G-Enabled Internet of Musical Things System

Turchet

Casari

2024

IEEE Internet Things J.

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The availability of high-performance embedded audio systems, along with high-bandwidth and low-latency connectivity options provided by 5G networks, is enabling the Internet of Musical Things (IoMusT) paradigm. A central component of this paradigm is represented by Networked Music Performances (NMPs), where geographically displaced musicians play together over the network in real time. However, to date, IoMusT deployments over 5G networks remain scarce, and very limited statistical results are available on the actual latency and reliability of 5G networks for IoMusT and NMP scenarios. In this paper, we present a private 5G IoMusT deployment and analyze its performance when supporting NMPs. Our IoMusT system is composed of up to four nodes and includes different background traffic conditions. We focused on the assessment of the sole wireless link, as the measurements can be easily transferred to a realistic NMP architecture involving a WAN by compounding them with those of the WAN. Our results show that latency increases with the number of nodes and with the presence of background traffic, whereas the reliability did not vary with the complexity of the conditions. For all tested scenarios, the average measured latency was below 24 ms (including a jitter buffer of 10.66 ms), whereas packet losses occurred with a probability of less than 0.01. However, irregular spikes were found for all latency and reliability metrics, which can significantly reduce the quality of service perceived by the users of NMP applications. Finally, packet loss and latency resulted to be uncorrelated, which suggests that they have different root causes.

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Section: Introductionmentioning

confidence: 99%

Latency and Reliability Analysis of a 5G-Enabled Internet of Musical Things System

Turchet

Casari

2024

IEEE Internet Things J.

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“…The definition of resilient implies that it is a set of multiple parameters (Fig. 1) that directly or indirectly affect the efficiency and stability of a given network [12,13].…”

Section: Introductionmentioning

confidence: 99%

“…Fig 12. Average ratio of signalling and data packets depending on the mobility of mobile nodes with a movement speed of 0 -2 m/s…”

mentioning

confidence: 99%

Resilient enhancements of routing protocols in MANET

Baumgartner,

Papaj,

Kurkina

et al. 2024

Peer-to-Peer Netw. Appl.

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Resilient of routing processes is one of the biggest challenges for data transmission in mobile networks without infrastructure. Communication under current routing protocols is through a communication path that, although the shortest, may not perform satisfactorily in terms of resilient. Routing and communication within such a path may take place using nodes that are malicious or inappropriate in the communication process due to malicious or poor technical state. This paper presents a new algorithm for various uses of mobile ad hoc networks not only in edge networks with infrastructure but also with the possibility of being used in the cloud solutions. We have modified decentralized blockchain technology and artificial intelligence using deep learning methods that have been implemented in routing processes. The objective of this algorithm was to select the most resilient communication path from the source to the destination node. Such a communication path selection consisted of selecting the nodes that were most suitable in terms of resilience, where the selection nodes was provided through a network and technical parameters. The key quality of service metrics, throughput, total delay, number of delivered signaling and data packets and the ratio between them were used to evaluate the proposed resilient routing algorithm. Modified resilient routing protocols achieved improvement in all the analyzed parameters compared to the original routing protocols. The improvement in these parameters led to an increase in the resilience of the routing process based on the actual data obtained from each node in the network and previous communications.

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Analysis of Temporal Robustness in Massive Machine Type Communications

Cited by 2 publications

References 47 publications

Latency and Reliability Analysis of a 5G-Enabled Internet of Musical Things System

Latency and Reliability Analysis of a 5G-Enabled Internet of Musical Things System

Resilient enhancements of routing protocols in MANET

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