Supporting quality of service in HTTP servers
PODC '98 Proceedings of the seventeenth annual ACM symposium on Principles of distributed computing
Analysis of Task Assignment Policies in Scalable Distributed Web-Server Systems
IEEE Transactions on Parallel and Distributed Systems
A scalable and highly available system for serving dynamic data at frequently accessed web sites
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Search and Progressive Image Retrieval from Distributed Image/Video Databases: The SPIRE Project
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Improving web server performance by caching dynamic data
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
Workload Characterization and Performance Implications of Large-Scale Blog Servers
ACM Transactions on the Web (TWEB)
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A fundamental trend for servers in network-centric computing environments is to evolve from traditional database and transaction servers to information distribution and handling systems. In addition to documents written in the HyperText Markup Language (HTML), data stored in other forms can be retrieved through the Common Gateway Interface (CGI). A significant performance bottleneck is the initialization and setup phase for a CGI process to gain access to a backend server. In this paper, we describe the design and implementation of distributed Web server for CGI processes to acquire services efficiently. A Connection Manager Daemon (CMD) is developed to provide a number of cliettes, which are connected to backend servers to eliminate initialization costs for incoming requests. A Cache Manager is implemented to speedup response time in case of repeated requests. We also trace and monitor the Connection Manager Daemon as well as its clients using extended UTE (Unified Trace Environment) tools, and present its performance analysis and visualization. The platforms where we conduct this study include a single-node workstation, a cluster of workstations, and an IBM Scalable Parallel (SP) system.