Measurement and modelling of self-similar traffic in computer networks

Classical Transmission Control Protocol (TCP) designs have never considered the identity of the competing transport protocol as useful information to TCP sources in congestion control mechanisms. When competing against a TCP flow on a bottleneck link, a User Datagram Protocol (UDP) flow can unfairly occupy the entire link bandwidth and suffocate all TCP flows on the link. If it were possible for a TCP source to know the type of transport protocol that deprives it of link access, perhaps it would be better for the TCP source to react in a way which prevents total starvation. In this paper, we use coefficient of variation and power spectral density of throughput traces to identify the presence of UDP transport protocols that compete against TCP flows on bottleneck links. Our results show clear traits that differentiate the presence of competing UDP flows from TCP flows independent of round-trip times variations. Signatures that we identified include an increase in coefficient of variation whenever a competing UDP flow joins the bottleneck link for the first time, noisy spectral density representation of a TCP flow when competing against a UDP flow in the bottleneck link, and a dominant frequency with outstanding power in the presence of TCP competition only. In addition, the results show that signatures for congestion caused by

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“…1. Despite the apparent simplicity, models with a single bottleneck node have been used in various works [7,22]. Infact in Ref.…”

Section: Simulation Setupmentioning

confidence: 99%

Towards end-host-based identification of competing protocols against TCP in a bottleneck link

Idris

Serwadda

2010

Ann. Telecommun.

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“…Metodę R/S dla ciągu wartości o skończonej długo-ści zarejestrowanych odstępów czasu pomiędzy zdarzeniami 1 2 , , , n t t t K definiujemy w następujący sposób [2,4,6,8].…”

Section: Wybrane Metody Wyznaczania Współczynnika Hurstaunclassified

Statistical analysis of the computer network operation in the LabVIEW environment

Dymora

Mazurek

Jaskółka

2015

ZN PRz Elektrotechnika

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Analiza ruchu sieciowego oraz metod wykrywania nieprawidłowości pracy urządzeń sieciowych stanowi ciekawy problem dla analityków badających sieci komputerowe. Poprawna interpretacja anomalii oraz odpowiednia reakcja na nie może poprawić jakość działania sieci, zapobiec awarii lub skrócić jej czas. W artykule przedstawiono oryginalną aplikację utworzoną w środowisku LabVIEW, z zaimplementowanymi algorytmami do wyznaczania współczynnika Hursta, będącego miarą samopodobieństwa i określenia zależności długoterminowych oraz multifraktalności ruchu sieciowego. Celem aplikacji było zaimplementowanie znanych metod wyznaczania współczynnika Hursta m.in. metody statystyki R/S, metody wartości bezwzględnej oraz zagregowanej wariancji -jako aparatu statystycznego do określenia cech ruchu sieciowego. W badaniach wykorzystano wirtualną sieć testową, której model utworzono w środowisku OPNET Modeler. Przeprowadzona w programie analiza statystyczna wskazała, że poziom samopodobieństwa ruchu sieciowego zawiera się w przedziale od 0,5 do 1, zaś jego wartość przybiera wyższe wartości wraz z rosnącym wypełnieniem pasma sieci. Nieprzerwany ruch sieciowy o małym natężeniu (np. ruch typu VoIP) posiada samopodobieństwo porównywalne do szumu białego równe 0,5 co zaprezentowano w artykule.Słowa kluczowe: współczynnik Hursta, wykrywanie anomalii sieci komputerowych, samopodobieństwo, zależności długoterminowe, systemy złożone.

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“…As network throughput and load gradually increases along with the prevalence of applications requiring some level of service from the network, as does the requirement to explore the way that these applications utilise the network. It is therefore becoming critical to understand the traffic sent over the network and the statistical analysis and modelling of applications offers an ideal solution for this [16].…”

Section: Related Workmentioning

confidence: 99%

Characterising a grid site's traffic

Elkhatib

Mackay

et al. 2010

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

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Grid computing has been widely adopted for intensive high performance computing. Since grid resources are distributed over complex large-scale infrastructures, understanding grid site data traffic behaviour is important for efficient resource utilisation, performance optimisation, and the design of future grid sites as well as traffic-aware grid applications. In this paper, we study and analyse the traffic generated at a grid site in the Large Hadron Collider (LHC) Computing Grid (LCG). We find that most of the generated traffic is TCP-based and that a small set of grid applications generate significant amounts of the data. Upon analysing the different traffic metrics, we also find that the traffic exhibits long-range dependence and self-similarity. We also investigate packet-level metrics such as throughput, packet rate, round trip time (RTT) and packet loss. Our study establishes that these metrics can be well represented by Gaussian mixture models. The findings we present in this paper will enable accurate grid site traffic monitoring and potentially on-the-fly traffic modelling and prediction. It will also lead to a better understanding of grid site's traffic behaviour and contribute to more efficient grid site planning, traffic management, data transmission protocol optimisation, and data-aware grid application design.

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Measurement and modelling of self-similar traffic in computer networks

Cited by 42 publications

References 30 publications

Towards end-host-based identification of competing protocols against TCP in a bottleneck link

Towards end-host-based identification of competing protocols against TCP in a bottleneck link

Statistical analysis of the computer network operation in the LabVIEW environment

Characterising a grid site's traffic

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