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Resource Management in Volunteer Computing Grids

Resource Management in Volunteer Computing Grids. An analysis of the different approaches to maximizing throughput on a BOINC grid. Presented by Geoffrey Oxholm and Beata Chrulkiewicz CS-575 Position Paper Presentation Fall 2007. Volunteer Grids. A Type of Grid Computer

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Resource Management in Volunteer Computing Grids

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  1. Resource Management in Volunteer Computing Grids An analysis of the different approaches to maximizing throughput on a BOINC grid Presented by Geoffrey Oxholm and BeataChrulkiewicz CS-575 Position Paper Presentation Fall 2007

  2. Volunteer Grids • A Type of Grid Computer • Decentralized, volunteer nodes • Supercomputing for free • 1.1 PetaFLOPS vs. 360 TeraFLOPS • Unreliable Nodes • Users can disconnect their computers anytime • Amount of donated resources is subject to change • Evil jerks can upload malicious data Image: http://www.di.unipi.it/groups/architetture/images/grid.gif http://holistic.com.mt/h/?Page=Article&Ref=107

  3. Berkeley Open Infrastructure for Network Computing • Duplicate work to ensure validity • R – The “Redundancy Factor” • Validate computation results. If the validation fails, repeat computation. • Validation Methods: • Majority Voting • More than R/2 nodes must agree • M-First Voting • First M nodes must agree Image: http://en.wikipedia.org/wiki/Image:BOINC_logo_July_2007.png

  4. Success and Limitations of BOINC • With proper configuration high throughput can be achieved • Still quite difficult to get volunteers • Proper configuration is difficult • Fixed configurations can not account for constantly changing grid characteristics Image: http://www.baseacid.com/imagesRR/workBand.jpg

  5. Fix: User Encouragement Feedback and Reward • Each node generates statistics • Teams can be formed • Sense of pride in commitment • Encourages users to donate more time, resources Team OCUK Predictor@home total credit. Go team! Image: http://teamocuk.com/cprojectcred1.php?p=PAH

  6. Fix: Maximizing Configuration Through Usage Simulation • Enumerate a set of possible configurations • Test configurations in a fraction of the time • Avoid disturbing volunteers by simulating • Zero in on an effective configuration Image: http://www.cyberroach.com/tron/tron3_circuit.jpg

  7. Fix: Dynamic Redundancy Through Reliability Prediction • Wait for a minimum number of nodes before assigning work • Choose nodes which have higher reliability • Higher reliability means less need for redundancy • Successful completion yields higher reliability rating for the node Image: http://image.compusa.com/prodimages/44/8537c95c-8027-4840-b976-67deb0690e13.gif

  8. Evaluation • User Encouragement • Encourages cheating • Does nothing to maximize efficient use of resources • Usage Simulation • Still requires researchers to configure system • Static configuration fails to match dynamic grid • Reliability Rating • Subject to further exploitation • Further minimizes the value of slow nodes, working against incentives Image: GPL Licensed

  9. Conclusion • Build on existing methods • Continue to encourage users • Create a starting point by using simulation • Update reliability system to avoid conflict with system of incentives • Develop new technologies • Blacklist malicious nodes • Develop a more comprehensive reliability system which uses past schedules to predict future availability Image: http://pixels.dessgeega.com/wp-content/uploads/2006/10/organize_big.gif

  10. Questions? Geoff Oxholm Beata Churkiewicz Image: http://www.grid.phys.uvic.ca/

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