Web prefetching in a mobile environment

Prefetching is one of the most popular techniques for dealing with the slow access speed of the World Wide Web. To provide a mobile user with effective real time online prefetching requires that the prefetch decision is able to adapt to different network systems. This article describes an adaptive network prefetch scheme which accomplishes this task. The basic scheme is comprised of a prediction module and a threshold module, which computes the access probabilities and prefetch thresholds respectively. The access probabilities indicate how likely files will be requested by the user, and the prefetch thresholds determine whether the performance may be improved by prefetching certain files. As a user changes network in a mobile environment, it is the prefetch threshold, which is computed based on system conditions as well as the costs of bandwidth and time, that adjusts the number of prefetched files accordingly. In addition, by extending the method of computing the access probabilities, we are able to prefetch a group of files together for a user who is about to be disconnected from the network.

[1]  Leonard Kleinrock,et al.  An adaptive network prefetch scheme , 1998, IEEE J. Sel. Areas Commun..

[2]  Srinivasan Seshan,et al.  SPAND: Shared Passive Network Performance Discovery , 1997, USENIX Symposium on Internet Technologies and Systems.

[3]  Srinivasan Seshan,et al.  Analyzing stability in wide-area network performance , 1997, SIGMETRICS '97.

[4]  Margo I. Seltzer,et al.  Autonomous replication across wide-area internetworks , 1995, SOSP.

[5]  Darrell D. E. Long,et al.  Exploring the Bounds of Web Latency Reduction from Caching and Prefetching , 1997, USENIX Symposium on Internet Technologies and Systems.

[6]  Umeshwar Dayal,et al.  From User Access Patterns to Dynamic Hypertext Linking , 1996, Comput. Networks.

[7]  Azer Bestavros,et al.  WWW traffic reduction and load balancing through server-based caching , 1997, IEEE Concurrency.

[8]  Geoffrey H. Kuenning,et al.  Automated hoarding for mobile computers , 1997, SOSP.

[9]  Jeffrey C. Mogul,et al.  Using predictive prefetching to improve World Wide Web latency , 1996, CCRV.

[10]  Anja Feldmann,et al.  Rate of Change and other Metrics: a Live Study of the World Wide Web , 1997, USENIX Symposium on Internet Technologies and Systems.

[11]  Azer Bestavros,et al.  Speculative data dissemination and service to reduce server load, network traffic and service time in distributed information systems , 1996, Proceedings of the Twelfth International Conference on Data Engineering.

[12]  Tomonari Kamba,et al.  Learning Personal Preferences on Online Newspaper Articles from User Behaviors , 1997, Comput. Networks.

[13]  Bill N. Schilit,et al.  Digestor: Device-Independent Access to the World Wide Web , 1997, Comput. Networks.

[14]  Hui Lei,et al.  An analytical approach to file prefetching , 1997 .

[15]  Steffen Rothkugel,et al.  World Wide Web caching: the application-level view of the Internet , 1997, IEEE Commun. Mag..

[16]  Bill N. Schilit,et al.  TeleWeb: Loosely Connected Access to the World Wide Web , 1996, Comput. Networks.

[17]  Eric A. Brewer,et al.  Reducing WWW Latency and Bandwidth Requirements by Real-Time Distillation , 1996, Comput. Networks.

[18]  Valérie Issarny,et al.  Providing Quality of Service over the Web: A Newspaper-Based Approach , 1997, Comput. Networks.

[19]  Fred Douglis,et al.  Optimistic deltas for WWW latency reduction , 1997 .

[20]  Jim Griffioen,et al.  Reducing File System Latency using a Predictive Approach , 1994, USENIX Summer.