Per-flow structure of losses in a finite-buffer queue

Chydziñski, Andrzej

doi:10.1016/j.amc.2022.127215

Cited by 2 publications

(5 citation statements)

References 24 publications

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“…This theorem was proven in Chydzinski (2022). Despite its rather long formulation, the theorem is straightforward in numerical calculations.…”

Section: Individual Flowsmentioning

confidence: 92%

“…Then, the burst ratio was studied in Chydzinski and Samociuk (2019), Chydzinski et al (2018b), Chydzinski (2022) using as model an overflowed buffer. In these studies, B was derived for a few kinds of Poisson streams.…”

Section: Related Workmentioning

confidence: 99%

“…In particular, the multiplexed burst ratio for single Poisson arrivals was found in Chydzinski and Samociuk (2019), while for batch Poisson arrivals in Chydzinski et al (2018b). The per-flow burst ratio for Poisson arrivals was derived in Chydzinski (2022). Moreover, in Samociuk et al (2019) the multiplexed burst ratio was studied experimentally in a real networking environment, i.e.…”

Section: Related Workmentioning

confidence: 99%

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Burst Ratio of Packet Losses in Individual Network Flows

Chydziñski¹,

Adamczyk²

2023

Informatica

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We study the burst ratio of packet loss processes in networking. This parameter characterizes the inclination of packet losses to form long, consecutive sequences. Such long sequences of losses may have a negative impact on multimedia streams, particularly those of real-time type. In packet networks, the burst ratio is often elevated due to overflows of packet buffers, which are present in all routers and switches. In the article, we investigate the burst ratio in the per-flow manner, i.e. individually for every flow of packets traversing a network node. We first confront all the per-flow burst ratios with each other, as well as with the burst ratio computed for the multiplexed traffic. Next, we study the influence of different features of the system on these burst ratios. In particular, the influence of rates of flows and their proportions, the standard deviation of interarrival times, the capacity of the buffer, the system load and the distribution of the service time, is studied. Special attention is paid to models with non-Poisson flows, which are not analytically tractable.

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“…This theorem was proven in Chydzinski (2022). Despite its rather long formulation, the theorem is straightforward in numerical calculations.…”

Section: Individual Flowsmentioning

confidence: 92%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Burst Ratio of Packet Losses in Individual Network Flows

Chydziñski¹,

Adamczyk²

2023

Informatica

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“…Analysing systems with BPP traffic allows for the inclusion of the actual number of traffic sources (e.g., network user devices) in analytical models. Single-service queuing systems are also under consideration [15][16][17][18][19][20], which is generally relevant for packet-level system analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Figure20. Average queue length in the system: V r = 50 AUs, V v = 10 AUs, V q = 6 AUs, R c = 15 AUs, t s,1 = 1 AU, t s,2 = 2 AUs, t a,1 = 2 AUs, t e,1 = 3 AUs.…”

mentioning

confidence: 99%

An Analytical Model of a System with Compression and Queuing for Selected Traffic Flows

Hanczewski,

Stasiak,

Weissenberg

2023

Electronics

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This article proposes a new analytical model of a queuing system to which a mixture of multi-service traffic is offered. The system under consideration has the advantage of servicing calls, in a shared server, of which only part will be placed in a queue when the server has no free resources (while the remaining part of the calls will be lost). In addition, this model also introduces the possibility for a compression mechanism to be applied for a selected number of data flows. The possibility of simultaneous analysis of the calls that can be placed in the queue as well as of those in which queuing is not implemented, while a certain number of them can be compressed, provides unquestionable advantage to the proposed model. The proposed model can be successfully applied to analyse and model 5G systems.

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Per-flow structure of losses in a finite-buffer queue

Cited by 2 publications

References 24 publications

Burst Ratio of Packet Losses in Individual Network Flows

Burst Ratio of Packet Losses in Individual Network Flows

An Analytical Model of a System with Compression and Queuing for Selected Traffic Flows

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