Using experience to guide Web server selection

Maria L. Gullickson; Catherine E. Eichholz; Ann L. Chervenak; Ellen W. Zegura

doi:10.1117/12.333805

14 December 1998 Using experience to guide Web server selection

Maria L. Gullickson, Catherine E. Eichholz, Ann L. Chervenak, Ellen W. Zegura

Proceedings Volume 3654, Multimedia Computing and Networking 1999; (1998) https://doi.org/10.1117/12.333805
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

We examine the use of the anycasting communication paradigm to improve client performance when accessing replicated multimedia objects. Anycasting supports dynamic selection of a server amongst a group of servers that provide equivalent content. It the selection is done well, the client will experience improved performance. A key issue in anycasting is the method used to maintain performance information used in server selection. We explore using past performance or experience to predict future performance. We conduct our work in the context of a customized web prefetching application called WebSnatcher. We examine a variety of algorithms for selecting a server using past performance and find that the overall average and weighted average algorithms are closest to optimal performance. In addition to the WebSnatcher application, this work has implications for responsible network behavior by other applications that generate network traffic automatically. By using the techniques we present here, such applications can reduce network and server load, potentially improving performance for interactive applications. The results can also be used to reach conclusions about the performance that would be obtained if anycasting were used in an interactive application.

Citation Download Citation

Maria L. Gullickson, Catherine E. Eichholz, Ann L. Chervenak, and Ellen W. Zegura "Using experience to guide Web server selection", Proc. SPIE 3654, Multimedia Computing and Networking 1999, (14 December 1998); https://doi.org/10.1117/12.333805

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available