USITS ‘01 The Age Penalty and its effect on cache performance Edith Cohen AT&T Labs-Research Haim Kaplan Tel-Aviv University Presenting: Edith Cohen.

Slides:



Advertisements
Similar presentations
Inktomi Confidential and Proprietary The Inktomi Climate Lab: An Integrated Environment for Analyzing and Simulating Customer Network Traffic Stephane.
Advertisements

Amazon CloudFront An introductory discussion. What is Amazon CloudFront? 5/31/20122© e-Zest Solutions Ltd. Amazon CloudFront is a web service for content.
1 Server Selection & Content Distribution Networks (slides by Srini Seshan, CS CMU)
Caching Strategies in Transcoding-Enabled Proxy System for Streaming Media Distribution Networks Bo Shen Sung-Ju Lee Sujoy Basu IEEE Transactions On Multimedia,
1 Content Delivery Networks iBAND2 May 24, 1999 Dave Farber CTO Sandpiper Networks, Inc.
Lecture 12, : The Internet, Summer : The Internet Lecture 12: Scalable services David O’Hallaron School of Computer Science and Department.
1 11 Web Caching Web Protocols and Practice. 2 Topics Web Protocols and Practice WEB CACHING  Cache Definition  Goals of Web Caching  Motivations for.
A Taxonomy and Survey of Content Delivery Networks Meng-Huan Wu 2011/10/26 1.
1 Caching in HTTP Representation and Management of Data on the Internet.
Web Caching Schemes1 A Survey of Web Caching Schemes for the Internet Jia Wang.
Internet Networking Spring 2006 Tutorial 12 Web Caching Protocols ICP, CARP.
The Effect of Consistency on Cache Response Time John Dilley and HP Laboratories IEEE Network, May-June 2000 Chun-Fu Kung System Laboratory Dept. of Computer.
An Analysis of Internet Content Delivery Systems Stefan Saroiu, Krishna P. Gommadi, Richard J. Dunn, Steven D. Gribble, and Henry M. Levy Proceedings of.
October 25, 2001Stanford Networking Seminar Aging Through Cascaded Caches: Performance Issues in the Distribution of Web Content. Edith Cohen AT&T Labs-research.
What’s a Web Cache? Why do people use them? Web cache location Web cache purpose There are two main reasons that Web cache are used:  to reduce latency.
1 Spring Semester 2007, Dept. of Computer Science, Technion Internet Networking recitation #13 Web Caching Protocols ICP, CARP.
CDNs & Replication Prof. Vern Paxson EE122 Fall 2007 TAs: Lisa Fowler, Daniel Killebrew, Jorge Ortiz.
Internet Networking Spring 2002 Tutorial 13 Web Caching Protocols ICP, CARP.
Implementing ISA Server Caching. Caching Overview ISA Server supports caching as a way to improve the speed of retrieving information from the Internet.
Caching And Prefetching For Web Content Distribution Presented By:- Harpreet Singh Sidong Zeng ECE Fall 2007.
1 Web Content Delivery Reading: Section and COS 461: Computer Networks Spring 2007 (MW 1:30-2:50 in Friend 004) Ioannis Avramopoulos Instructor:
Web Caching Schemes For The Internet – cont. By Jia Wang.
Web Caching and CDNs March 3, Content Distribution Motivation –Network path from server to client is slow/congested –Web server is overloaded Web.
The Medusa Proxy A Tool For Exploring User- Perceived Web Performance Mimika Koletsou and Geoffrey M. Voelker University of California, San Diego Proceeding.
1 ENHANCHING THE WEB’S INFRASTUCTURE: FROM CACHING TO REPLICATION ECE 7995 Presented By: Pooja Swami and Usha Parashetti.
Caching and Content Distribution Networks. Web Caching r As an example, we use the web to illustrate caching and other related issues browser Web Proxy.
Web Cache. Introduction what is web cache?  Introducing proxy servers at certain points in the network that serve in caching Web documents for faster.
Content Distribution Network (CDN) Performance Punit Shah CSE581 Internet Technologies OGI, OHSU 2002, Jan 16th.
Information-Centric Networks05a-1 Week 5 / Paper 1 On the use and performance of content distribution networks –Balachander Krishnamurthy, Craig Wills,
1 Content Distribution Networks. 2 Replication Issues Request distribution: how to transparently distribute requests for content among replication servers.
Caching and Content Distribution Networks. Some Interesting Observations r Top 1 % of all documents account for 20% - 35% of proxy requests r Top 10%
On the Use and Performance of Content Distribution Networks Balachander Krishnamurthy Craig Wills Yin Zhang Presenter: Wei Zhang CSE Department of Lehigh.
1 Caching  Temporary storage of frequently accessed data (duplicating original data stored somewhere else)  Reduces access time/latency for clients 
Content Distribution March 8, : Application Layer1.
1 3 Web Proxies Web Protocols and Practice. 2 Topics Web Protocols and Practice WEB PROXIES  Web Proxy Definition  Three of the Most Common Intermediaries.
Caching for Sustainability Alex Bunch. Agenda Intro Overview Background Analysis Implementation Future.
Web Caching: Replication on the World Wide Web Jonathan Bulava CSC8530 – Distributed Systems Dr. Paul Schragger.
Design and Implement an Efficient Web Application Server Presented by Tai-Lin Han Date: 11/28/2000.
SAINT ‘01 Proactive DNS Caching: Addressing a Performance Bottleneck Edith Cohen AT&T Labs-Research Haim Kaplan Tel-Aviv University.
Web Caching Dr. Yingwu Zhu. What is Web Caching Introducing proxy servers at certain points in the network that serve in caching Web documents for faster.
User-Perceived Latency zLong perceived latency is the most serious WWW performance problem The delay from the time a request is issued until response is.
Web Caching and Content Distribution: A View From the Interior Syam Gadde Jeff Chase Duke University Michael Rabinovich AT&T Labs - Research.
Refreshment Policies for Web Content Caches Edith Cohen AT&T Labs-Research Haim Kaplan Tel-Aviv University Presenting: Edith Cohen.
Dr. Yingwu Zhu Summary Cache : A Scalable Wide- Area Web Cache Sharing Protocol.
1 Lifetime Behavior and its Impact on Web Caching X. Chen and P. Mohapatra, IEEE Workshop on Internet Applications (WIAPP), 김호중, CA Lab. Site 별,
1 Caching in HTTP Representation and Management of Data on the Internet.
Module 9: Implementing Caching. Overview Caching Overview Configuring General Cache Properties Configuring Cache Rules Configuring Content Download Jobs.
A Survey on Network Storage Ning Zong Haibin Song Richard Alimi Richard Yang.
World Wide Web Caching CS457 Seminar Yutao Zhong 11/13/2001.
HTTP support for caching & replication. Conditional requests Server executes conditional request. Responds with a message body only if the condition is.
ICP and the Squid Web Cache Duanc Wessels k Claffy August 13, 1997 元智大學系統實驗室 宮春富 2000/01/26.
Web Cache Consistency. “Requirements of performance, availability, and disconnected operation require us to relax the goal of semantic transparency.”
Computer Science Lecture 14, page 1 CS677: Distributed OS Last Class: Concurrency Control Concurrency control –Two phase locks –Time stamps Intro to Replication.
On The Cooperation of Web Clients and Proxy Caches Yiu Fai Sit, Francis C.M. Lau, Cho-Li Wang Department of Computer Science The University of Hong Kong.
HTTP evolution - TCP/IP issues Lecture 4 CM David De Roure
Implementing ISA Server Caching
Content Distribution Network, Proxy CDN: Distributed Environment
Information-Centric Networks Section # 5.1: Content Distribution Instructor: George Xylomenos Department: Informatics.
Content Delivery Networks: Status and Trends Speaker: Shao-Fen Chou Advisor: Dr. Ho-Ting Wu 5/8/
1 COMP 431 Internet Services & Protocols HTTP Persistence & Web Caching Jasleen Kaur February 11, 2016.
Overview on Web Caching COSC 513 Class Presentation Instructor: Prof. M. Anvari Student name: Wei Wei ID:
THE FUTURE IS HERE: APPLICATION- AWARE CACHING BY ASHOK ANAND.
Proxy Caching for Streaming Media
Caching Temporary storage of frequently accessed data (duplicating original data stored somewhere else) Reduces access time/latency for clients Reduces.
Ad-blocker circumvention System
Web Caching? Web Caching:.
Internet Networking recitation #12
ECE 671 – Lecture 16 Content Distribution Networks
On the Use and Performance of Content Distribution Networks
CSE 461 HTTP and the Web.
Presentation transcript:

USITS ‘01 The Age Penalty and its effect on cache performance Edith Cohen AT&T Labs-Research Haim Kaplan Tel-Aviv University Presenting: Edith Cohen

USITS ‘01 Distribution of Web Content Origin server cache Content of URL can be modified by the origin. Copies are cached throughout

USITS ‘01 HTTP Freshness Control Cached copies have: –Freshness lifetime –Age (elapsed time since fetched from origin) TTL (Time to Live) = freshness lifetime – age Expired copies must be validated before they can be used. Body (content) header Cache-directives

USITS ‘01 HTTP Cache Serving a Request No cached copy  GET a fresh copy   Stale cached copy  If-Modified-Since GET a fresh copy “Not-Modified”  update header   “Modified”  update content and header   Fresh cached copy   GET

USITS ‘01 “hits” and “misses” hit-rate metric: c-hit/(c-hit+c-miss) latency (c-miss) > latency (f-miss) >> latency (f-hit)   “hit-rate” does not capture freshness freshness-rate: f-hit/c-hit f-hitf-missc-miss remote RTTs XX content-transfer X “traditional”: c-hit ( hit )( miss )

USITS ‘01 “Value” of a Cached Copy Frequency/pattern of requests Size (storage cost) Fetching cost (latency/bandwidth) Modification rate (likelihood of c-miss) Age (likelihood of f-miss) Important issues for: replacement and pre-fetching strategies cascaded caches

USITS ‘01 Origin Server to User reverse proxy proxy cache AS

USITS ‘01 Issues for Cascaded Caches Path between Web server and end-user often includes 2 or more caches.  downstream cache sends older copies  more misses at upstream caches – more traffic between caches – increased user-perceived latency

USITS ‘01 1:00pm Freshness-lifetime= 10 H Age = 0 Distributing Copies Origin server downstream cache upstream cache 7:00pm Freshness-lifetime= 10 H Age = 6 H Freshness-lifetime= 10 H Age = 9:59 H 10:59pm

USITS ‘01 Modeling Sources of a Cache “Cache” misses are forwarded to a cache Cache-2 Cache Cache-1 “Origin” misses are forwarded to authoritative (origin) server.

USITS ‘01 Source Models… origin: age(t) = 0 cache: age(t) = T - (t+ a ) mod T Object with freshness-lifetime = T. The age of copy retrieved at time t is: Theorem: miss_origin(S) < miss_cache(S) < 2*miss_origin(S) Request sequence S Age-Penalty Definition:

USITS ‘01 …Age-penalty Requests: cache T t TTL origin mf-mh m

USITS ‘01 Trace-driven Simulations log OriginCachepenalty NLANR UC52%43%21% NLANR SD47%38%24% freshness-rate for different configurations

USITS ‘01 CDN server Content Delivery Network AS

USITS ‘01 Content Delivery Networks CDN servers are a system of reverse proxy caches, placed throughout the Internet. Proprietary, non-HTTP, freshness control between origin and CDN servers, allowing for longer TTL durations. CDN Cache HTTP freshness control Proprietary freshness control

USITS ‘01 CDN Age-Handling Practices Practice: “Intact headers” CDN servers act as a cache, end-to-end headers are intact. (-3/2000). What are the implications? Practice: “emulate origin” CDN servers rewrite age to 0 (3/2000-present) Practice: “equate lifetime” CDN servers rewrite HTTP freshness lifetime is equated (extended) to “proprietary” freshness lifetime. How much can be gained?

USITS ‘01 …Implications of Intact Headers  Age = time on CDN server  copies often served with 0 TTL!

USITS ‘01 …Implications of Intact Headers CDNNLANR log %requestsFreshness-rate CDNorigin SandpiperUC0.4%5%76% SandpiperSD0.5%6%67% AkamaiUC1.7%5%61% AkamaiSD1.1%6%63%

USITS ‘01 …..Equating Lifetimes How much can be gained? We estimate about 20% of requests to CDN (Akamai) servers would be eliminated.

USITS ‘01 Conclusion Content-aging can have significant performance effect on cascaded Web caches (25% decrease in effectiveness of cache hits). Aging effects are not being carefully accounted for (see CDN practices). Content-aging warrants more awareness by practitioners, and more research...

USITS ‘01 Follow-up Work More “source” types (e.g., alternating between several downstream caches) Pre-term refreshes by downstream cache (sporadic updates by downstream cache may decrease performance, but this can be avoided) Longer lifetime durations at upstream caches (tradeoff of staleness and latency) Rejuvenation by downstream caches (refresh “fresh” popular copies to set their age to 0). Proper use can improve performance, but otherwise can decrease performance (!!!)…