1. CIS 6930.008: Internet-Scale Networked Systems Adriana Iamnitchi (Anda) anda@cse.usf.edu

2. 2 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Contact Info Email: anda@cse.usf.edu Office: ENB 334 Office hours: Wed 2-4 and by appointment (email me) Course page: http://www.csee.usf.edu/~anda/cis6930.008

3. 3 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) CIS 6930.008: Course Goals l Primary –Gain deep understanding of fundamental issues that affect design of large-scale federated distributed systems –Map primary contemporary research themes –Gain experience in distributes systems research l Secondary –By studying a set of outstanding papers, build knowledge of how to present research –Learn how to read papers & evaluate ideas

4. 4 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) What I’ll Assume You Know l Basic Internet architecture –IP, TCP, DNS, HTTP l Basic principles of distributed computing –Asynchrony (cannot distinguish between communication failures and latency) –Partial global state knowledge (cannot know everything correctly) –Failures happen. In very large systems, even rare failures happen often l If there are things that don’t make sense, ask!

5. 5 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Examples of Distributed Systems ATT webGnutella network The Internet A Sensor Network

6. 6 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Definition (a version) l A distributed system is a collection of autonomous, programmable, failure-prone entities that are able to communicate through a communication medium that is unreliable. –Entity=a process on a device (PC, PDA, mote) –Communication Medium=Wired or wireless network l “Internet-Scale”: – Spanning multiple institutional or network (DNS) domains –(Much) Larger than “cluster”

7. 7 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) This semester’s Theme (a proposal) Exploiting Emergent Behavior in Large-Scale Distributed Systems

8. Filecules and Small Worlds in a Scientific Workload: Characteristics and Significance

9. 9 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Grid: Resource-Sharing Environment l Users: –1000s from 10s institutions –Well-established communities l Resources: –Computers, data, instruments, storage, applications –Owned/administered by institutions l Applications: data- and compute- intensive processing l Approach: common infrastructure

10. 10 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) The Problem l We have now: –Mature grid deployments running in production mode l We do not have yet: –Quantitative characterization of real workloads. >How many files, how much input data per process, etc. –And thus, benchmarks, workload models, reproducible results l Costs: –Local solutions, often replicating work –“Temporary” solutions that become permanent –Far from optimal solutions –Impossible to compare alternatives on relevant workloads

11. 11 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Still, Why Should We Care? Partial TopologyRandom 30% dieTargeted 4% die from Saroiu et al., MMCN 2002 l Impossibility results, high costs: Tradeoffs are necessary –Solution: Select tradeoffs based on >User requirements (of course) >Usage patterns l Patterns exist and can be exploited. Examples: –Zipf distribution for request popularity (web caching) Breslau et al., Infocom’99 –Network topology:

12. 12 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) The DØ Experiment l High-energy physics data grid l 72 institutions, 18 countries, 500+ physicists l Detector Data –1,000,000 Channels –Event rate ~50 Hz –So far, 1.9 PB of data l Data Processing –Signals: physics events –Events about 250 KB, stored in files of ~1GB –Every bit of raw data is accessed for processing/filtering –Past year overall: 0.6 PB l DØ: –… processes PBs/year –… processes 10s TB/day –… uses 25% – 50% remote computing

13. Filecules and Small Worlds in Scientific Communities: Characteristics and Significance Joint work with Matei Ripeanu (UBC) and Ian Foster (ANL and UChicago)

14. 14 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) “No 24 in B minor, BWV 869” “Les Bonbons” “ Yellow Submarine” “Les Bonbons” “Yellow Submarine” “Wood Is a Pleasant Thing to Think About” “Wood Is a Pleasant Thing to Think About” New metric: The Data-Sharing Graph G m T (V, E):  V is set of users active during interval T  An edge in E connects users that asked for at least m common files within T

15. 15 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Small average path length Large clustering coefficient The DØ Collaboration Small World! CCoef = # Existing Edges # Possible Edges 6 months of traces (January – June 2002) 300+ users, 2 million requests for 200K files

16. 16 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Small-World Graphs l Small path length, large clustering coefficient –Typically compared against random graphs l Think of: –“It’s a small world!” –“Six degrees of separation” l Milgram’s experiments in the 60s l Guare’s play “Six Degrees of Separation”

17. 17 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Other Small Worlds Word co-occurrences Film actors LANL coauthors Internet Web Food web Power grid D. J. Watts and S. H. Strogatz, Collective dynamics of small-world networks. Nature, 393:440-442, 1998 R. Albert and A.-L. Barabási, Statistical mechanics of complex networks, R. Modern Physics 74, 47 (2002).

18. 18 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Web Data-Sharing Graphs 7200s, 50files 3600s, 50files 1800s, 100files 1800s, 10file 300s, 1file Data-Sharing Relationships in the Web, Iamnitchi, Ripeanu, and Foster, WWW’03

19. 19 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) DØ Data-Sharing Graphs 7days, 1file 28 days, 1 file

20. 20 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) KaZaA Data-Sharing Graphs 7day, 1file 28 days 1 file 2 hours 1 file 1 day 2 files 4h 2 files 12h 4 files Small-World File-Sharing Communities, Iamnitchi, Ripeanu, and Foster, Infocom ‘04

21. 21 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) D0 Web Kazaa Interest-Aware Information Dissemination in Small-World Communities, Iamnitchi and Foster, HPDC’05 Interest-Aware Data Dissemination

22. 22 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Tracking User Attention in Collaborative Tagging Communities, Elizeu Santos-Neto, Matei Ripeanu, and Adriana Iamnitchi, Workshop on Contextualized Attention Metadata (CAMA'07), Vancouver, Canada, June 2007. Current Work: Tagging Communities

23. D Ø Workload Characterization Joint work with Shyamala Doraimani (USF) and Gabriele Garzoglio (FNAL)

24. 24 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) DØ Traces l Traces from January 2003 to May 2005 l 234,000 jobs, 561 users, 34 domains, 1.13 million files accessed l 108 input files per job on average l Detailed data access information about half of these jobs (113,062)

25. 25 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Contradicts Traditional Models File size distribution l Expected: log-normal. Why not? –Deployment decisions –Domain specific –Data transformation File popularity distribution l Expected: Zipf. Why not? (speculations): l Scientific data is uniformly interesting l User community is relatively small

26. 26 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Filecules: Intuition

27. 27 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Filecules: General Characteristics Filecules in High-Energy Physics: Characteristics and Impact on Resource Management, Adriana Iamnitchi, Shyamala Doraimani, Gabriele Garzoglio, HPDC’06

28. 28 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Filecules: Size Filecules of different sizes: l Largest filecule:17 TB or 51,841 files l 28% mono-file filecules

29. 29 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Consequences for Caching l Use filecule membership for prefetching –When a file is missing from the local cache, prefetch the entire filecule l Use time locality in cache replacement –Least Recently Used (classic algorithm) l Implemented: –LRU with files and LRU with filecules –Greedy Request Value: prefetching + job reordering >Does not exploit temporal locality >Prefetching based on cache content –Our variant of LRU with filecules and job reordering E. Otoo, et al. Optimal file-bundle caching algorithms for data-grids. In SC ’04

30. 30 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Comparison: Caching Algorithms (1)

31. 31 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Comparison: Caching Algorithms (2) % of cache change is a measure of transfer costs.

32. 32 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Summary Part 1 l Revisited traditional workload models –Generalized from file systems, the web, etc. –Some confirmed (temporal locality), some infirmed (file size distribution and popularity) l Compared caching algorithms on D0 data: –Temporal locality is relevant –Filecules guide prefetching

33. 33 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Summary l Workload characterization based on a HEP grid –Quantify scale (data processed, number of files) –Contradict traditional models l Patterns can guide system design –Filecules: caching, data replication –Small world data sharing: adaptive information dissemination, replica placement

34. 34 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Paper Reviewing (1) l Goals: –Think of what you read –Get used to writing paper reviews l Reviews due by noon before class l Be professional in your writing l Have an eye on the writing style: –Clarity –Beware of traps: learn to use them in writing and detect them in reading –Detect (and stay away from) trivial claims. E.g., 1 st sentence in the Introduction: “The tremendous/unprecedented/phenomenal growth/scale/ubiquity of the Internet…”

35. 35 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Paper Reviewing (2) Follow the form provided when relevant. l State the main contribution of the paper l Critique the main contribution: Rate the significance of the paper on a scale of 5 (breakthrough), 4 (significant contribution), 3 (modest contribution), 2 (incremental contribution), 1 (no contribution or negative contribution). Explain your rating in a sentence or two. Rate how convincing the methodology is. l Do the claims and conclusions follow from the experiments? l Are the assumptions realistic? l Are the experiments well designed? l Are there different experiments that would be more convincing? l Are there other alternatives the authors should have considered? l (And, of course, is the paper free of methodological errors?)

36. 36 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Paper Reviewing (3) l What is the most important limitation of the approach? l What are the three strongest and/or most interesting ideas in the paper? l What are the three most striking weaknesses in the paper? l Name three questions that you would like to ask the authors. l Detail an interesting extension to the work not mentioned in the future work section. l Optional comments on the paper that you’d like to see discussed in class.

37. 37 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Discussion leading l Come prepared! –Prepare discussion outline –Prepare questions: >“What if”s >Unclear aspects of the solution proposed >… –Similar ideas in different contexts –Initiate short brainstorming sessions l Leaders do NOT need to submit paper reviews l Main goals: –Keep discussion flowing –Keep discussion relevant –Engage everybody (I’ll have an eye on this, too)

38. 38 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Projects l Combine with your research if relevant to the class l Get approval from all instructors if you overlap final projects: –Don’t sell the same piece of work twice –You can get more than twice as many results with less than twice as much work l Aim high! –Put one extra month and get a publication out of it –It is doable (we have proofs) l Try ideas that you postponed out of fear: it’s just a class, not your PhD.

39. 39 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Administravia: Project deadlines (tentative) l January 30: 1-page project proposal l Feb. 26: 3-page literature survey –Know relevant work in your problem area –If implementation project, list tools, similar projects l March 31: 5-page Midterm project due –Have a clear image of what’s possible/doable –Report preliminary results l Last class:In-class project presentation –Demo, if appropriate l May 1: –Final report due

40. 40 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Next Classed l Lectures on basics of distributed systems l Will start reading papers in about 2 weeks

41. 41 CIS6930.008: Internet-Scale Networked Systems (Spring 2008) Questions?