Characterization of E-commerce traffic

The World Wide Web has acheived immense popularity in the business world. It is thus essential to characterize the traffic behavior at these sites, a study that will facilitate the design and development of high-performance, reliable e-commerce servers. This paper makes an effort in this direction. Aggregated traffic arriving at a Business-to-Business (B2B) and a Business-to-Consumer (B2C) e-commerce site was collected and analyzed. A high degree of self-similarity was found in the traffic (higher than that observed in general Web-environment). Heavy-tailed behavior of transfer times was established at both the sites. Traditionally, this behavior has been attributed to the distribution of transfer sizes, which was not the case in B2C space. This implies that the heavy-tailed transfer times are actually caused by the behavior of back-end service time. In B2B space, transfer-sizes were found to be heavy-tailed. A detailed study of the traffic and load at the back-end servers was also conducted and the inferences are included in this paper.

[1]  Mark Crovella,et al.  Self - similarity in World Wide Web: Evidence and possible causes , 1997 .

[2]  Robert J. Glushko,et al.  An XML framework for agent-based E-commerce , 1999, CACM.

[3]  Patrice Abry,et al.  A Wavelet-Based Joint Estimator of the Parameters of Long-Range Dependence , 1999, IEEE Trans. Inf. Theory.

[4]  Virgílio A. F. Almeida,et al.  Business-oriented resource management policies for e-commerce servers , 2000, Perform. Evaluation.

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

[6]  Rick Floyd Short-Term File Reference Patterns in a UNIX Environment, , 1986 .

[7]  Mandyam M. Srinivasan,et al.  Introduction To Computer System Performance Evaluation , 1992 .

[8]  Krishna Kant,et al.  Server Capacity Planning for Web Traffic Workload , 1999, IEEE Trans. Knowl. Data Eng..

[9]  Prasant Mohapatra,et al.  An Admission Control Scheme for Predictable Server Response Time for Web Accesses , 2001, WWW '01.

[10]  Jerome A. Rolia,et al.  Predicting the QoS of an electronic commerce server: those mean percentiles , 1998, PERV.

[11]  Whitfield Diffie E-commerce and security , 1998, STAN.

[12]  John Kunze,et al.  A trace-driven analysis of the unix 4 , 1985, SOSP 1985.

[13]  Virgílio A. F. Almeida,et al.  Capacity Planning for Web Performance: Metrics, Models, and Methods , 1998 .

[14]  Zafer Sahinoglu,et al.  On multimedia networks: self-similar traffic and network performance , 1999, IEEE Commun. Mag..

[15]  Moses Ma Agents in E-commerce , 1999, CACM.

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

[17]  Virgílio A. F. Almeida,et al.  Resource management policies for e-commerce servers , 2000, PERV.