A client-aware dispatching algorithm for web clusters providing multiple services
Proceedings of the 10th international conference on World Wide Web
The state of the art in locally distributed Web-server systems
ACM Computing Surveys (CSUR)
Cluster Computing
Content-Aware Dispatching Algorithms for Cluster-Based Web Servers
Cluster Computing
A Tiered System for Serving Differentiated Content
World Wide Web
Architecting Web sites for high performance
Scientific Programming
Scalable, distributed data structures for internet service construction
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
CSP: a novel system architecture for scalable internet and communication services
USITS'01 Proceedings of the 3rd conference on USENIX Symposium on Internet Technologies and Systems - Volume 3
Balancing HTTP traffic using dynamically updated weights, an implementation approach
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
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We study design alternatives for, and describe implementations and performance of, a scalable and highly available Web server accelerator. The accelerator runs under an embedded operating system and improves Web server performance by caching data. The basic design alternatives include a content router or a TCP router (without content routing) in front of a set of Web cache accelerator nodes, with the cache memory distributed across the accelerator nodes. Content based routing reduces cache node CPU cycles but can make the front-end router a bottleneck. With the TCP router, a request for a cached object may initially be sent to the wrong cache node; this results in larger cache node CPU cycles, but can provide a higher aggregate throughput, because the TCP router becomes a bottleneck at a higher throughput than the content router. Based on measurement of implementations, we quantify the throughput ranges in which different designs are preferable. We also examine a combination of content based and TCP routing techniques. We examine optimizations, such as different communication and data delivery methods, replication of hot objects, and cache replacement policies that take into account the fact that there might be different bottlenecks in the system at different times; depending upon which resource is likely to become a bottleneck, a different cache replacement algorithm is applied.