Adaptive replication for web applications
DSM '04 Proceedings of the 1st international doctoral symposium on Middleware
Workflow-based resource allocation to optimize overall performance of composite services
Future Generation Computer Systems
Efficient application placement in a dynamic hosting platform
Proceedings of the 18th international conference on World wide web
A survey on dynamic Web content generation and delivery techniques
Journal of Network and Computer Applications
Distributed redirection for the World-Wide Web
Computer Networks: The International Journal of Computer and Telecommunications Networking
ICA3PP'07 Proceedings of the 7th international conference on Algorithms and architectures for parallel processing
Distributed workload and response time management for web applications
Proceedings of the 7th International Conference on Network and Services Management
Towards transparent and distributed workload management for large scale web servers
Future Generation Computer Systems
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Many Web-based commercial services deliver their content using Web applications that generate pages dynamically based on user profiles, request parameters etc. The workload of these applications are often characterized by a large number of unique requests and a significant fraction of data updates. Hosting these applications drives the need for systems that replicates both the application code and its underlying data. We propose the design of such a system that is based on on-demand replication, where data units are replicated only to servers that access them often. This reduces the consistency overhead as updates are sent to a reduced number of servers. The proposed system allows complete replication transparency to the application, thereby allowing developers to build applications unaware of the underlying data replication. We show that the proposed techniques can reduce the client response time by a factor of 5 in comparison to existing techniques for a real-world e-commerce application used in the TPC-W benchmark. Furthermore, we evaluate our strategies for a wide range of workloads and show that on-demand replication performs better than centralized and fully replicated systems by reducing the average latency of read/write data accesses as well as the amount of bandwidth utilized to maintain data consistency.