Using predictive prefetching to improve World Wide Web latency
ACM SIGCOMM Computer Communication Review
Web prefetching between low-bandwidth clients and proxies: potential and performance
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Link prediction and path analysis using Markov chains
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
A New Markov Model For Web Access Prediction
Computing in Science and Engineering
A Data Mining Algorithm for Generalized Web Prefetching
IEEE Transactions on Knowledge and Data Engineering
Exploiting Webspace Organization for Accelerating Web Prefetching
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
An Experimental Framework for Testing Web Prefetching Techniques
EUROMICRO '04 Proceedings of the 30th EUROMICRO Conference
Improving the performance of client web object retrieval
Journal of Systems and Software
Modeling continuous changes of the user's dynamic behavior in the WWW
Proceedings of the 5th international workshop on Software and performance
Objective-Optimal Algorithms for Long-Term Web Prefetching
IEEE Transactions on Computers
Object prefetching using semantic links
ACM SIGMIS Database
Web prefetching performance metrics: a survey
Performance Evaluation
The Impact of the Web Prefetching Architecture on the Limits of Reducing User's Perceived Latency
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
NPS: a non-interfering deployable web perfectching system
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
A user-focused evaluation of web prefetching algorithms
Computer Communications
An online PPM prediction model for web prefetching
Proceedings of the 9th annual ACM international workshop on Web information and data management
Mining web logs to improve hit ratios of prefetching and caching
Knowledge-Based Systems
A clustering-based prefetching scheme on a Web cache environment
Computers and Electrical Engineering
A PPM Prediction Model Based on Stochastic Gradient Descent for Web Prefetching
AINA '08 Proceedings of the 22nd International Conference on Advanced Information Networking and Applications
Temporal pre-fetching of dynamic web pages
Information Systems
Short Survey: A taxonomy of web prediction algorithms
Expert Systems with Applications: An International Journal
Watching user generated videos with prefetching
Image Communication
A comparison of prediction algorithms for prefetching in the current web
Journal of Web Engineering
Efficient ad-hoc search for personalized PageRank
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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Web prefetching is a technique aimed at reducing user-perceived latencies in the World Wide Web. The spatial locality shown by user accesses makes it possible to predict future accesses from the previous ones. A prefetching engine uses these predictions to prefetch web objects before the user demands them. The existing prediction algorithms achieved an acceptable performance when they were proposed but the high increase in the number of embedded objects per page has reduced their effectiveness in the current web. In this paper, we show that most of the predictions made by the existing algorithms are not useful to reduce the user-perceived latency because these algorithms do not take into account the structure of the current web pages, i.e., an HTML object with several embedded objects. Thus, they predict the accesses to the embedded objects in an HTML after reading the HTML itself. For this reason, the prediction is not made early enough to prefetch the objects and, therefore, there is no latency reduction. In this paper we present the double dependency graph (DDG) algorithm that distinguishes between container objects (HTML) and embedded objects to create a new prediction model according to the structure of the current web. Results show that, for the same number of extra requests to the server, DDG reduces the perceived latency, on average, 40% more than the existing algorithms. Moreover, DDG distributes latency reductions more homogeneously among users.