Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
IEEE Transactions on Computers
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SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
IEEE Transactions on Software Engineering
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ANSS '05 Proceedings of the 38th annual Symposium on Simulation
Experiment and analysis for QoS of E-commerce systems
Journal of Theoretical and Applied Electronic Commerce Research
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The cycle time of an Internet based online shopper includes time at an electronic commerce (e-commerce) server to gather information and purchase products, download time to transfer data over the Internet, and think time for interpreting the results of individual requests. Currently most home based shoppers are limited to 56.6K modems and have cycle times largely determined by download time. Mega-bit (Mb) modems will soon be commonplace and will cause a significant reduction in the download time component of the shopper cycle time. This gain in download time can be utilized by the shoppers to submit additional requests to the server during their cycle times leading to an increased overall load on the server. The purpose of this paper is to consider the impact of higher shopper bandwidths on the performance of web-based shopping servers. To start with, we study the contents of several professionally managed e-commerce sites to obtain measures that include average page size and measures of mall size. The performance of a demonstration shopping mall system is measured under a controlled load to obtain optimistic measures of resource demands for such sites. An analytic model is developed and validated with respect to the measured system. The model is then modified to predict the behavior of both small and large shopping mall sites as client access to bandwidth and Internet performance increases.