![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
Reduction of Monitoring Registers on Software Defined Networks
Characterization of data network monitoring registers allows for reductions in the number of data, which is essential when the information flow is high, and implementation of processes with short response times, such as interchange of control information between devices and anomaly detection is required. The present investigation applied wavelet transforms, so as to characterize the statistic monitoring register of a software-defined network. Its main contribution lies in the obtention of a record that, although reduced, retains detailed, essential information for the correct application of anomaly detectors.
Keywords
Characterization, Wavelet Transform, Network Monitoring, Anomaly Detectors, Software-Defined Networking (SDN).
User
Font Size
Information
- Ibidunmoye, Olumuyiwa, Hernandez R Francisco, Elmroth Erick .(2015) “Performance Anomaly Detection and Bottleneck Identification”. ACM Computing Surveys, Vol. 48, No. 1, Article 4.
- M, Jammal, T. Singh, A. Shami, R.l Asal, Y. Li, (2014) "Software defined networking: State of the art and research challenges", Computer Networks.
- Dabbagh, B.Hamdaoui, M. Guizani, and A. Rayes,(2015) "Software-Defined Networking Security: Pros and Cons", IEEE Communications Magazine.
- N, S. Bailey, Deepak Bansal, Linda Dunbar, Dave Hood, Zoltán Lajos Kis, (2012) "SDN Architecture Overview”. Open Network Foundation. (https://www.opennetworking.org/images/stories/downloads/sdn-resources/technical- reports/SDN-architecture-overview-1.0.pdf)
- K. Giotis, C. Argyropoulos, G. Androulidakis, D. Kalogeras, V. Maglaris, (2014) "Combining OpenFlow and sFlow for an effective and scalable anomaly detection and mitigation mechanism on SDN environments”, Computer pag. 122–136
- L. Jose, M. Yu, and J. Rexford, (2011) “Online measurement of large traffic aggregates on commodity switches”, in Proc. of the USENIX workshop.
- Stéphane. Mallat, (2008) “A wavelet tour of signal processing”. Academic Press, USA.
- L. Kalinichemko, I. Shanin, I. Taraban,(2014) "Methods for Anormaly Detection: a Survey", Advanced Methodos and Technologies, digital collections. Pag. 20-25.
- J. Uthayakumar, T.Vengattaraman, P. Dhavachelvan (2018) “A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications” Journal of King Saud University – Computer and Information Sciences. Pags. 1-22
- L.A. Aristizábal (2009). “Paralell implementation for Generalized Method 1-D Biosignal Compession” World Academic of Science, Engineering and Technology.
- L.A. Aristizábal, C. Cortes, R, Flórez (2008).”ECG signal noise reduction and compression for remote diagnosis systems”. INTER-NOISE Congress Proceedings. Pags 4130-4135.
- K. Kyriakopoulos, D.J. Parish (2009). “Using Wavelets for Compression and Detecting Events in Anomalous Network Traffic”. Fourth International Conference on Systems and Networks Communications. IEEE Xplore.
- A. Al-Jawad, P. Shah, O. Gemikonakli, R. Trestian.(2016). “Compression-based technique for SDN using sparse-representation dictionary”. IEEE/IFIF Network Operations and Management Symposium.
- A. Cortes. (2018) “Simulation of Software Define Networks with Open Network Operating System and Mininet”. International Journal of Computer Science and Information Technology. (IJCSIT). Vol 10. Nro. 5. Pags 21-32.
- M. Dabagh, B. Handaoul, M. Guizani, A. Rayes, (2015) "Software-Defined Networking Security: Pro and Cons”, IEEE Communications Magazine. pags. 73-79.
- L. Seunghyeon, K. Jinwoo, S. Seungwon, P. Porras, (2017). “Athena: A framework for scalable Anormaly Detection in Software Defined Networks”,47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks. Pags 249-260.
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 226
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 121