Towards an Automatic Modeling Tool for Observed System Behavior

Current computer systems and communication networks tend to be highly complex, and they typically hide their internal structure from their users. Thus, for selected aspects of capacity planning, overload control and related applications, it is useful to have a method allowing one to find good and relatively simple approximations for the observed system behavior. This paper investigates one such approach where we attempt to represent the latter by adequately selecting the parameters of a set of queueing models. We identify a limited number of queueing models that we use as Building Blocks in our procedure. The selected Building Blocks allow us to accurately approximate the measured behavior of a range of different systems. We propose an approach for selecting and combining suitable Building Blocks, as well as for their calibration. We are able to successfully validate our methodology for a number of case studies. Finally, we discuss the potential and the limitations of the proposed approach.

[1]  Leonard Kleinrock,et al.  Theory, Volume 1, Queueing Systems , 1975 .

[2]  Toshikazu Kimura,et al.  Approximations for multi-server queues: System interpolations , 1994, Queueing Syst. Theory Appl..

[3]  Serge Fdida,et al.  A framework for interpreting measurement over Internet , 2003, MoMeTools '03.

[4]  Balachander Krishnamurthy,et al.  Internet Measurement - Infrastructure, Traffic, and Applications , 2006 .

[5]  Alejandro Quintero,et al.  Performance evaluation of a broadband wireless access system subjected to heavy load , 2004, Comput. Commun..

[6]  Maria Kihl,et al.  Web server performance modeling using an M/G/1/K*PS queue , 2003, 10th International Conference on Telecommunications, 2003. ICT 2003..

[7]  Katya Scheinberg,et al.  Recent progress in unconstrained nonlinear optimization without derivatives , 1997, Math. Program..

[8]  Donald F. Towsley,et al.  Inferring network characteristics via moment-based estimators , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[9]  Jia Wang,et al.  Efficient and accurate Ethernet simulation , 1999, Proceedings 24th Conference on Local Computer Networks. LCN'99.

[10]  Philip Heidelberger,et al.  Computer Performance Evaluation Methodology , 1984, IEEE Transactions on Computers.

[11]  Guangwei Bai,et al.  Analytical modeling of primary and secondary load as induced by video applications using UDP/IP , 2002, Comput. Commun..

[12]  Bernd E. Wolfinger,et al.  A unified load generator based on formal load specification and load transformation , 2006, valuetools '06.

[13]  Arif Merchant,et al.  Issues and challenges in the performance analysis of real disk arrays , 2004, IEEE Transactions on Parallel and Distributed Systems.

[14]  J. S. Kaufman Approximation methods for networks of queues with priorities , 1984, Perform. Evaluation.

[15]  Leonard Kleinrock,et al.  Queueing Systems: Volume I-Theory , 1975 .

[16]  Stephen A. Jarvis,et al.  A dynamic predictive framework for e-business workload management , 2003 .

[17]  Zhen Liu,et al.  Parameter inference of queueing models for IT systems using end-to-end measurements , 2006, Perform. Evaluation.

[18]  David R. Anderson,et al.  Bayesian Methods in Cosmology: Model selection and multi-model inference , 2009 .

[19]  Alexandre Brandwajn,et al.  A conditional probability approach to M/G/1-like queues , 2008, Perform. Evaluation.

[20]  A. L. Scherr,et al.  AN ANALYSIS OF TIME-SHARED COMPUTER SYSTEMS , 1965 .

[21]  Arnold O. Allen,et al.  Probability, statistics and queueing theory - with computer science applications (2. ed.) , 1981, Int. CMG Conference.

[22]  Alexandre Brandwajn,et al.  Equivalence and Decomposition in Queueing Systems - A Unified Approach , 1985, Perform. Evaluation.

[23]  Frank Kelly,et al.  Reversibility and Stochastic Networks , 1979 .

[24]  Vern Paxson,et al.  Measurements and analysis of end-to-end Internet dynamics , 1997 .