1 / 17

Improving End-to-End Performance of the Web Using Server Volumes and Proxy Filters

Improving End-to-End Performance of the Web Using Server Volumes and Proxy Filters. Edith Cohen, Balachander Krishnamurthy, and Jennifer Rexford ACM SIGCOMM Conference 1998 전산학과 CALab 황인철. Contents. Introduction Exchanging Filter and Volume Information Server Volumes

karis
Download Presentation

Improving End-to-End Performance of the Web Using Server Volumes and Proxy Filters

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Improving End-to-End Performance of the Web Using Server Volumes and Proxy Filters Edith Cohen, Balachander Krishnamurthy, and Jennifer Rexford ACM SIGCOMM Conference 1998 전산학과 CALab 황인철

  2. Contents • Introduction • Exchanging Filter and Volume Information • Server Volumes • Web Proxy Applications • Conclusion • Discussion

  3. Introduction(1/2) • The exponential rate of growth of the WWW • A dramatic increase in Internet traffic • A significant degradation in user-perceived latency

  4. Introduction(2/2) • Previous research for these problems • Focused on improving the performance of individual components • Without considering any other components • In this paper • Focuses on end-to-end information exchange by piggybacking • Between the proxy and the server

  5. Exchanging Filter and Volume Information- Piggybacking Protocol(1/3) • The server • Has the information about each resource, including size and content type as well as the frequency of modification • The proxy • Has the information about its domain of clients and their access pattern • To bridge the knowledge gap between servers and proxies • piggybacking

  6. Exchanging Filter and Volume Information- Piggybacking Protocol(2/3) • Server volume • The group of related resources at server-side • Proxy filter • The method to tailor volume information

  7. Exchanging Filter and Volume Information- Piggybacking Protocol(3/3)

  8. Exchanging Filter and Volume Information- Proxy Filters • Problem of piggybacking protocol • If several accesses occur to the same server, server transfers the same information • The method to reduce piggybacked message using proxy filter • Proxy can control piggyback frequency • Randomized Method • RPV(Recently Piggybacked volumes) • Proxy can customize the contents of each piggyback messages

  9. Exchanging Filter and Volume Information- Piggybacking in HTTP 1.1 Proxy -> Server Server -> Proxy

  10. Server Volumes- Optimization Criteria • Fraction predicted • The probability that a resource requested at the proxy has appeared in at least one piggyback message in the last T seconds • True prediction fraction • The likelihood that a resource that appears in a piggyback message will be accessed by a client in the next T seconds • Update fraction • The likelihood that a resource requested at the proxy has been predicted in the last T seconds and appeared in a previous request in the last C seconds, where C>T

  11. Server Volumes- Directory-Based Volumes • Volume Construction and Maintenance • Based on the heuristic • Resources in the same directory are likely to have related content • Example • One-level volume • www.foo.com/a/b.html & www.foo.com/a/d/e.html • www.foo.com/a/b.html & www.foo.com/c/k.html • Volume elements • A collection of FIFO lists partitioned by resource size and content type

  12. Server Volumes- Probability-Based Volumes • Volume Construction and Maintenance • Construct volume by measuring access patterns • Resource s is included in r’s volume if Ps|r >= Pt

  13. Server Volumes- Performance Evaluation Directory-based Probability-based

  14. Server Volumes- Performance Evaluation Directory-based Probability-based

  15. Web Proxy Applications • Cache coherency • Prefetching • Cache replacement • Adaptive freshness interval

  16. Conclusions • Using piggyback message • The information can exchange among the various Web components • Server volume • Directory-based • Probability-based

  17. Discussion • Good approach • Proxy uses the server-side information • Evaluation • In Real Web Proxy Application • New research for • The proxy filters

More Related