Detecting Overlapping Community Structures in Networks
World Wide Web
Evaluating the utility of content delivery networks
Proceedings of the 4th edition of the UPGRADE-CN workshop on Use of P2P, GRID and agents for the development of content networks
Towards a semantic self-organising web page-ranking mechanism using computational geometry
MAMECTIS'08 Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems
Using common Lisp to prototype offline work in web applications for rich domains
Proceedings of the 6th European Lisp Workshop
CDNsim: A simulation tool for content distribution networks
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Using current web page structure to improve prefetching performance
Computer Networks: The International Journal of Computer and Telecommunications Networking
International Journal of Knowledge and Web Intelligence
Content delivery and caching from a network provider's perspective
Computer Networks: The International Journal of Computer and Telecommunications Networking
Review: A survey on content-centric technologies for the current Internet: CDN and P2P solutions
Computer Communications
Short Survey: A taxonomy of web prediction algorithms
Expert Systems with Applications: An International Journal
A comparison of prediction algorithms for prefetching in the current web
Journal of Web Engineering
Distributed top-k full-text content dissemination
Distributed and Parallel Databases
A case for virtualization of content delivery networks
Proceedings of the Winter Simulation Conference
Community detection for proximity alignment
Integrated Computer-Aided Engineering
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Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the "edge" of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the "last mile" latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of "correlated" Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity.