Traffic modeling and performance analysis of commercial web sites

With the rapid advances in Internet technology, e-commerce is becoming a mature business strategy. The concept of Quality of ~ l.* ' ~ ' ~ Service (QoS) is working its way to the front lines of e-business ~ 1.2 commitments and requirements as it plays an important role in In~ 1 ternet applications, services and pricing negotiations. One needs to ~ 0.s have a fundamental understanding of the key characteristics of the 0.6 0.4 workload patterns in commercial Web sites and a fundamental un:~ 0.2 derstanding of the impact of such workload patterns on Web server ~ 0 , , , performance as well as the server capacity required to guarantee

[1]  Zhen Liu,et al.  Traffic model and performance evaluation of Web servers , 2001, Perform. Evaluation.

[2]  Patrice Abry,et al.  Wavelet Analysis of Long-Range-Dependent Traffic , 1998, IEEE Trans. Inf. Theory.

[3]  Walter Willinger,et al.  Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level , 1997, TNET.

[4]  Mark E. Crovella,et al.  Effect of traffic self-similarity on network performance , 1997, Other Conferences.

[5]  Mark S. Squillante,et al.  Web traffic modeling and Web server performance analysis , 1999, PERV.

[6]  Allen B. Downey The structural cause of file size distributions , 2001, SIGMETRICS '01.

[7]  Mark S. Squillante,et al.  Analysis and characterization of large‐scale Web server access patterns and performance , 1999, World Wide Web.

[8]  Carey L. Williamson,et al.  Internet Web servers: workload characterization and performance implications , 1997, TNET.

[9]  Anja Feldmann,et al.  The changing nature of network traffic: scaling phenomena , 1998, CCRV.

[10]  Sidney I. Resnick,et al.  Heavy Tail Modelling and Teletraffic Data , 1995 .

[11]  Walter Willinger,et al.  Self-Similarity in High-Speed Packet Traffic: Analysis and Modeling of Ethernet Traffic Measurements , 1995 .

[12]  S. Resnick Heavy tail modeling and teletraffic data: special invited paper , 1997 .

[13]  M. Crovella,et al.  Estimating the Heavy Tail Index from Scaling Properties , 1999 .

[14]  Martin F. Arlitt,et al.  Web server workload characterization: the search for invariants , 1996, SIGMETRICS '96.

[15]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1996, SIGCOMM '96.

[16]  A. Pakes ON THE TAILS OF WAITING-TIME DISTRIBUTIONS , 1975 .

[17]  Nick Duffield,et al.  Large deviations and overflow probabilities for the general single-server queue, with applications , 1995 .

[18]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[19]  Virgílio A. F. Almeida,et al.  A methodology for workload characterization of E-commerce sites , 1999, EC '99.

[20]  Sally Floyd,et al.  Wide-area traffic: the failure of Poisson modeling , 1994 .

[21]  Mark S. Squillante,et al.  Web traffic modeling and Web server performance analysis , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[22]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.

[23]  Rudolf H. Riedi,et al.  Multifractal Properties of TCP Traffic: a Numerical Study , 1997 .

[24]  Jan Beran,et al.  Statistics for long-memory processes , 1994 .

[25]  LiuZhen,et al.  Traffic model and performance evaluation of Web servers , 2001 .

[26]  Paul Barford,et al.  Generating representative Web workloads for network and server performance evaluation , 1998, SIGMETRICS '98/PERFORMANCE '98.

[27]  Ilkka Norros,et al.  A storage model with self-similar input , 1994, Queueing Syst. Theory Appl..