Characterizing Web Response Time

(ABSTRACT) It is critical to understand WWW latency in order to design better HTTP protocols. In this study we characterize Web response time and examine the effects of proxy caching, network bandwidth, traffic load, persistent connections for a page, and periodicity. Based on studies with four workloads, we show that at least a quarter of the total elapsed time is spent on establishing TCP connections with HTTP/1.0. The distributions of connection time and elapsed time can be modeled using Pearson, Weibul, or Log-logistic distributions. We also characterize the effect of a user's network bandwidth on response time. Average connection time from a client via a 33.6 K modem is two times longer than that from a client via switched Ethernet. We estimate the elapsed time savings from using persistent connections for a page to vary from about a quarter to a half. Response times display strong daily and weekly patterns. This study finds that a proxy caching server is sensitive to traffic loads. Contrary to the typical thought about Web proxy caching, this study also finds that a single stand-alone squid proxy cache does not always reduce response time for our workloads. Implications of these results to future versions of the HTTP protocol and to Web application design also are discussed. Acknowledgments I thank Professor Edward A. Fox, my advisor, for his advice, help and support during my thesis and throughout my graduate program in the Department of Computer Science at Virginia Tech. I also thank the members of my advisory committee Professor Marc Abrams and Professor Roger W. Enrich for their comments and suggestions. Help and suggestions from other members of the Network Research Group (NRG) at Virginia Tech including Ghaleb Abdulla and Tommy Johnson also are appreciated. Grants from IBM and the National Science Foundation (NCR-9627922) partially supported my graduate study. IBM donated the equipment used to collect the traffic log files, conduct experiments and analyze the data. Finally, many thanks go to Wen Wang, my wife and Andy Liu, my son for their understanding and support during the course of my graduate studies.