Web applications are becoming increasingly popular for mobile wireless systems. However, wireless networks can have high packet loss rates, which can degrade web browsing performance on wireless systems. An alternative approach is wireless thin-client computing, in which the web browser runs on a remote thin server with a more reliable wired connection to the Internet. A mobile client then maintains a connection to the thin server to receive display updates over the lossy wireless network. To assess the viability of this thin-client approach, we compare the web browsing performance of thin clients against fat clients that run the web browser locally in lossy wireless networks. Our results show that thin clients can operate quite effectively over lossy networks. Compared to fat clients running web browsers locally, our results show surprisingly that thin clients can be faster and more resilient on web applications over lossy wireless LANs despite having to send more data over the network. We characterize and analyze different design choices in various thin-client systems and explain why these approaches can yield superior web browsing performance in lossy wireless networks.

Modern thin-client systems are designed to provide the same graphical interfaces and applications available on traditional desktop computers while centralizing administration and allowing more efficient use of computing resources. Despite the rapidly increasing popularity of these client-server systems, there are few reliable analyses of their performance. Industry standard benchmark techniques commonly used for measuring desktop system performance are ill-suited for measuring the performance of thin-client systems because these benchmarks only measure application performance on the server, not the actual user-perceived performance on the client. To address this problem, we have developed slow-motion benchmarking, a new measurement technique for evaluating thin-client systems. In slow-motion benchmarking, performance is measured by capturing network packet traces between a thin client and its respective server during the execution of a slow-motion version of a conventional benchmark application. These results can then be used either independently or in conjunction with conventional benchmark results to yield an accurate and objective measure of the performance of thin-client systems. We have demonstrated the effectiveness of slow-motion benchmarking by using this technique to measure the performance of several popular thin-client systems in various network environments on Web and multimedia workloads. Our results show that slow-motion benchmarking solves the problems with using conventional benchmarks on thin-client systems and is an accurate tool for analyzing the performance of these systems.