Abstract
Experimental network research is subject to challenges since the experiment outcomes can be influenced by undesired effects from other activities in the network. In shared experiment networks, control over resources is often limited and QoS guarantees might not be available. When the network conditions vary during a series of experiment unwanted artifacts can be introduced in the experimental results, reducing the reliability of the experiments. We propose a novel, systematic, methodology where network conditions are monitored during the experiments and information about the network is collected. This information, known as metadata, is analyzed statistically to identify periods during the experiments when the network conditions have been similar. Data points collected during these periods are valid for comparison. Our hypothesis is that this methodology can make experiments more reliable. We present a proof-of-concept implementation of our method, deployed in the FEDERICA and PlanetLab networks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Albrecht, J.: Achieving experiment repeatability on planetlab. In: NSF Workshop on Archiving Experiments to Raise Scientific Standards, NSF (2010)
Bickel, P.: A distribution free version of the smirnov two sample test in the p-variate case. The Annals of Mathematical Statistics 40(1), 1–23 (1969)
Cottrell, R.L.: Evaluation of techniques to detect significant network performance problems using End-to-End active network measurements. Technical report, NASA Center for AeroSpace Information (2006)
Ferrari, D., Zhou, S.: An empirical investigation of load indices for load balancing applications. Defense Technical Information Center (1987)
Fukunaga, K.: Introduction to statistical pattern recognition. Academic Pr. (1990)
Gelper, S., Fried, R., Croux, C.: Robust forecasting with exponential and Holt-Winters smoothing. Journal of Forecasting 29(3), 285–300 (2010)
Guralnik, V., Srivastava, J.: Event detection from time series data. In: Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 33–42. ACM (1999)
Hagsand, O.: Meter v2.2.2, http://www.nada.kth.se/~olofh/meter/ (accessed October 19, 2011)
Jones, E., Oliphant, T., Peterson, P.: SciPy: Open source scientific tools for Python (2001), http://www.scipy.org/ (accessed October 19, 2011)
Lee, S.-J., Sharma, P., Banerjee, S., Basu, S., Fonseca, R.: Measuring Bandwidth Between PlanetLab Nodes. In: Dovrolis, C. (ed.) PAM 2005. LNCS, vol. 3431, pp. 292–305. Springer, Heidelberg (2005)
Liao, T.W.: Clustering of time series data–a survey. Pattern Recognition 38(11), 1857–1874 (2005)
Massey, F.J.: The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association 46(253), 68–78 (1951)
McGregor, A.J., Braun, H.W.: Automated event detection for active measurement systems. In: Proceedings of PAM 2001 (2001)
Montgomery, D.: Design and analysis of experiments. John Wiley & Sons Inc. (2008)
Olsson, R.: Pktgen the linux packet generator. In: Linux Symposium 2005 (2005)
Park, K., Pai, V.S.: CoMon: a mostly-scalable monitoring system for PlanetLab. SIGOPS Operating Systems Review 40(1), 65–74 (2006)
Paxson, V.: Strategies for sound internet measurement. In: Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement, pp. 263–271. ACM (2004)
Peterson, L., Roscoe, T.: The design principles of PlanetLab. SIGOPS Operating Systems Review 40(1), 11–16 (2006)
Rahm, E., Do, H.H.: Data cleaning: Problems and current approaches. IEEE Bulletin on Data Engineering, 3 (2000)
Roscoe, T.: 33. The PlanetLab Platform. In: Steinmetz, R., Wehrle, K. (eds.) P2P Systems and Applications. LNCS, vol. 3485, pp. 567–581. Springer, Heidelberg (2005)
Rosenbaum, P.: An exact distribution-free test comparing two multivariate distributions based on adjacency. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67(4), 515–530 (2005)
Seibert, J., Zage, D., Fahmy, S., Nita-Rotaru, C.: Experimental comparison of peer-to-peer streaming overlays: An application perspective. In: Proceedings of the the 33rd IEEE Conference on Local Computer Networks, pp. 20–27 (2008)
Sollins, K.: RFC 1350: The TFTP protocol (Revision 2) (1992)
Sommers, J., Barford, P.: An active measurement system for shared environments. In: Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, IMC 2007, pp. 303–314. ACM, New York (2007)
Spring, N., Peterson, L., Bavier, A., Pai, V.: Using PlanetLab for network research: myths, realities, and best practices. ACM SIGOPS Operating Systems Review 40(1), 24 (2006)
Szegedi, P., Riera, J., Garcia-Espin, J., Hidell, M., Sjodin, P., Soderman, P., Ruffini, M., O’Mahony, D., Bianco, A., Giraudo, L., et al.: Enabling future internet research: the federica case. IEEE Communications Magazine 49(7), 54–61 (2011)
Wang, G., Ng, T.: The impact of virtualization on network performance of amazon ec2 data center. In: 2010 Proceedings IEEE INFOCOM, pp. 1–9. IEEE (2010)
Whiteaker, J., Schneider, F., Teixeira, R.: Explaining packet delays under virtualization. SIGCOMM Comput. Commun. Rev. 41, 38–44
Wijk, J.J.V., Selow, E.R.V.: Cluster and calendar based visualization of time series data. In: Infovis, p. 4. IEEE Computer Society (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Söderman, P., Hidell, M., Sjödin, P. (2012). Using Metadata to Improve Experiment Reliability in Shared Environments. In: Pescapè, A., Salgarelli, L., Dimitropoulos, X. (eds) Traffic Monitoring and Analysis. TMA 2012. Lecture Notes in Computer Science, vol 7189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28534-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-28534-9_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28533-2
Online ISBN: 978-3-642-28534-9
eBook Packages: Computer ScienceComputer Science (R0)