Abstract
Any application, database server, telephony server, or operating system maintains different states for their internal elements and resources. When tracing is enabled on such systems, the corresponding events in the trace logs can be used to extract and model the different state values of the traced modules to analyze their runtime behavior. In this paper, a generic method and corresponding data structures are proposed to model and manage the system state values, allowing efficient storage and access. The proposed state organization mechanism generates state intervals from trace events and stores them in a tree-based state history database. The state history database can then be used to extract the state of any system resources (i.e. cpu, process, memory, file, etc.) at any timestamp. The extracted state values can be used to track system problems (e.g. performance degradation). The proposed system is usable in both the offline tracing mode, when there is a set of trace files, and online tracing mode, when there is a stream of trace events. The proposed system has been implemented and used to display and analyze interactively various information extracted from very large traces in the magnitude order of 1 TB.
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
Cohen, I., Goldszmidt, M., Kelly, T., Symons, J., Chase, J.S.: Correlating instrumentation data to system states: A building block for automated diagnosis and control. In: Proceedings of the 6th Conference on Symposium on Operating Systems Design Implementation, vol. 6, p. 16. USENIX Association, Berkeley (2004)
Chan, A., Gropp, W., Lusk, E.: An efficient format for nearly constant-time access to arbitrary time intervals in large trace files. Scientific Programming 16(2), 155–165 (2008)
Cohen, I., Zhang, S., Goldszmidt, M., Symons, J., Kelly, T., Fox, A.: Capturing, indexing, clustering, and retrieving system history. SIGOPS Operating Systems Review 39(5), 105–118 (2005)
Desnoyers, M., Dagenais, M.R.: The LTTng tracer: A low impact performance and behavior monitor for GNU/Linux. In: Proceedings of the Ottawa Linux Symposium (2006)
Desnoyers, M., Dagenais, M.: LTTng: Tracing across execution layers, from the hypervisor to user-space. In: Proceedings of the Ottawa Linux Symposium (2008)
Ezzati-Jivan, N., Dagenais, M.R.: A stateful approach to generate synthetic events from kernel traces. In: Advances in Software Engineering (April 2012)
Ezzati-Jivan, N., Dagenais, M.R.: A framework to compute statistics of system parameters from very large trace files. SIGOPS Oper. Syst. Rev. 47(1), 43–54 (2013)
Giraldeau, F., Desfossez, J., Goulet, D., Dagenais, M., Desnoyers, M.: Recovering system metrics from kernel trace. In: Linux Symposium, p. 109 (June 2011)
Gaede, V., Gunther, O.: Multidimensional access methods. ACM Computing Surveys 30(2), 170–231 (1998)
Montplaisir, A.: Stockage sur disque pour acceés rapide d’ attributs avec intervalles de temps. Master’s thesis, Ecole polytechnique de Montreal (2011)
Schnorr, L.M., Huard, G., Navaux, P.O.A.: Towards visualization scalability through time intervals and hierarchical organization of monitoring data. In: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGRID 2009, pp. 428–435. IEEE Computer Society, Washington, DC (2009)
Zaki, O., Lusk, E., Gropp, W., Swider, D.: Toward scalable performance visualization with jumpshot. International Journal of High Performance Computing Applications 13(3), 277–288 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Montplaisir, A., Ezzati-Jivan, N., Wininger, F., Dagenais, M. (2013). Efficient Model to Query and Visualize the System States Extracted from Trace Data. In: Legay, A., Bensalem, S. (eds) Runtime Verification. RV 2013. Lecture Notes in Computer Science, vol 8174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40787-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-40787-1_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40786-4
Online ISBN: 978-3-642-40787-1
eBook Packages: Computer ScienceComputer Science (R0)