L_msrmnt.sp11 - CS 525 Advanced Distributed Systems Spring...

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1 CS 525 Advanced Distributed Systems Spring 2011 Indranil Gupta (Indy) Measurement Studies April 12, 2011 All Slides © IG Acknowledgments: Some slides by Long Vu, Jay Patel
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We’ve seen a variety of distributed systems so far… P2P file sharing systems (Kazaa, Gnutella, etc.) Clouds (AWS, etc.) P2P streaming systems (PPLive etc.) Often, the behavior and characteristics of these systems, when deployed in the wild, are surprising. Important to know these in order to build better distributed systems for deployment 2
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3 How do you find characteristics of these Systems in Real-life Settings? Write a crawler to crawl a real working system Collect traces from the crawler Tabulate the results Papers contain plenty of information on how data was collected, the caveats, ifs and buts of the interpretation, etc. These are important, but we will ignore them for this lecture and concentrate on the raw data and conclusions
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4 Measurement, Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload Gummadi et al Department of Computer Science University of Washington
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5 What They Did 2003 paper analyzed 200-day trace of Kazaa traffic Considered only traffic going from U. Washington to the outside Developed a model of multimedia workloads
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6 Results Summary 1. Users are patient 2. Users slow down as they age 3. Kazaa is not one workload 4. Kazaa clients fetch objects at-most-once 5. Popularity of objects is often short-lived 6. Kazaa is not Zipf
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7 User characteristics (1) Users are patient
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8 User characteristics (2) Users slow down as they age clients “die” older clients ask for less each time they use system
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9 User characteristics (3) Client activity Tracing used could only detect users when their clients transfer data Thus, they only report statistics on client activity, which is a lower bound on availability Avg session lengths are typically small (median: 2.4 mins ) Many transactions fail Periods of inactivity may occur during a request if client cannot find an available peer with the object
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10 Object characteristics (1) Kazaa is not one workload This does not account for connection overhead
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11 Object characteristics (2) Kazaa object dynamics Kazaa clients fetch objects at most once Popularity of objects is often short-lived Most popular objects tend to be recently-born objects Most requests are for old objects (> 1 month) 72% old – 28% new for large objects 52% old – 48% new for small objects
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12 Object characteristics (3) Kazaa is not Zipf Zipf’s law: popularity of i th-most popular object is proportional to i , (α: Zipf coefficient) Web access patterns are Zipf Authors conclude that Kazaa is not Zipf because of the at-most-once fetch characteristics Caveat: what is an “object” in Kazaa?
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13 Model of P2P file-sharing workloads [?] Why a model? On average, a client requests 2 objects/day
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This note was uploaded on 12/08/2011 for the course CS 525 taught by Professor Gupta during the Spring '08 term at University of Illinois, Urbana Champaign.

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L_msrmnt.sp11 - CS 525 Advanced Distributed Systems Spring...

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