Long-range dependence in DataCenter networks transmission

• Autorzy: Paszkiewicz A. , Bolanowski M.
• Języki publikacji: EN

Abstrakty

EN

The paper presents the mechanisms of long-range dependence measurement in the context of data transmission in Data Center networks. The research involved mainly analyzing network traffic generated by protocols such as CIFS and iSCSI, which are commonly used in such infrastructures. The purpose of the paper was to determine whether the network traffic of above mentioned protocols encapsulated in TCP/IP protocol will have persistent, anti-persist, or random walk character. By indicating long-range dependencies for this type of network traffic, it will be possible to develop effective mechanisms for detecting anomaly in its transmission as well as flow control, including QoS mechanisms, load balancing, etc.

Słowa kluczowe

EN

Hurst exponen; long-term memory; network convergence; data center protocols

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2017
• Tom: Vol. 63, No. 8
• Strony: 275--277
• Opis fizyczny: Bibliogr. 14 poz., rys., tab., wykr., wzory

Twórcy

autor

Paszkiewicz A.

• Department of Complex Systems, The Faculty of Electrical and Computer Engineering, Rzeszów University of Technology Rzeszów, Poland

autor

Bolanowski M.

• Department of Complex Systems, The Faculty of Electrical and Computer Engineering, Rzeszów University of Technology Rzeszów, Poland

Bibliografia

• [1] Nicolis G., Nicolis C.: Foundations of Complex Systems: Emergence, Information and Predicition. World Scientific Publishing Co., Singapure, 2012.
• [2] Grabowski F., Paszkiewicz A., Bolanowski M.: Computer Networks as Complex Systems in Nonextensive Approach. Journal of Applied Computer Science, vol. 21, No. 2, pp. 31-44, 2013.
• [3] Domańska J., Domańska A., Czachórski T.: A Few Investigations of Long-Range Dependence in Network Traffic. In: Proceedings of the 29th International Symposium on Computer and Information Sciences, Springer International Publishing, pp. 137-144, 2014.
• [4] Bolanowski M., Paszkiewicz A., Wroński M., Żegleń R.: Representativeness analysis and possible applications of partial network data flows. Measurement Automation Monitoring, t. 62, z. 1, s. 29-32, 2016.
• [5] Bolanowski M., Paszkiewicz A., Zapała P., Żak R.: Stress test of network devices with maximum traffic load for second and third layer of ISO/OSI model. Pomiary Automatyka Kontrola, t. 60, z. 10, s. 854-857, 2014.
• [6] Nunes B. A. A., Mendonca M., Nguyen X. N., Obraczka K., Turletti T.: A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks. IEEE Communications Surveys & Tutorials, vol. 16, issue 3, pp. 1617-1634, 2016.
• [7] Bolanowski M., Paszkiewicz A.: Nowy model detekcji zagrożeń w sieci komputerowej, Przegląd Elektrotechniczny, t. 89, z. 11, s. 308-311, 2013.
• [8] Tate J., Beck P., Ibarra H. H., Kumaravel S., Miklas L.: Introduction to Storage Area Networks. An IBM Redbooks publication, 2016.
• [9] Grabowski F.: Nonextensive model of self-organizing systems. Complexity, vol. 18, issue 5, pp. 28-36, 2013.
• [10] Ciftlikli C., Gezer A.: Comparison of Daubechies wavelets for Hurst parameter estimation. Turk J Elec Eng & Comp Sci, vol. 18, pp. 117-128. 2010.
• [11] Sheng H., Chen Y. Q., Qiu T. S.: Fractional Processes and Fractional-Order Signal Processing: Techniques and applications. Signals and Communication Technology, Springer, 2011.
• [12] Karagiannis T., Faloutsos M., Riedi R. H.: Long-Range Dependence: Now you see it, now you don’t! Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.
• [13] https://www.ixiacom.com/products/ixchariot. Access: 10.07.2017.
• [14] Gomółka Z., Twaróg B., Bartman J., Kwiatkowski B.: Improvement of Image Processing by Using Homogeneous Neural Networks with Fractional Derivatives Theorem, AIMS, Discrete and Continuous Dynamical Systems, Journal of American Institute of Mathematical Sciences, pp. 505-514, 2011.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).