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Addressing Strategic Behavior in a Deployed Microeconomic Resource Allocator

Addressing Strategic Behavior in a Deployed Microeconomic Resource Allocator. Chaki Ng (Harvard) Co-Authors: Phil Buonadonna, Brent Chun (Intel Research), Alex C. Snoeren, Amin Vahdat (UCSD) Other members: Alvin AuYoung (UCSD), David C. Parkes (Harvard). p2pecon’05.

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Addressing Strategic Behavior in a Deployed Microeconomic Resource Allocator

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  1. Addressing Strategic Behavior in a Deployed Microeconomic Resource Allocator Chaki Ng (Harvard) Co-Authors: Phil Buonadonna, Brent Chun (Intel Research), Alex C. Snoeren, Amin Vahdat (UCSD) Other members: Alvin AuYoung (UCSD), David C. Parkes (Harvard) p2pecon’05

  2. Pitching markets to systems folks “Markets don’t work” • …but they do provide efficiency “Gaming isn’t important” • …but it adds complexity • Need more experimental data • We deployed a system and observed usage

  3. Mirage testbed 150 nodes @ Intel

  4. Why testbed • Many users from different projects • Diverse resource requirements • Valuation varies • Resource contention can be serious

  5. Initial approach • Greedy first-price combinatorial auction • Expressive language for space/time • Non-sealed and modifiable bidding • Virtual currency policy

  6. Bidding interface

  7. 1:00 3:00 4:00 5:00 2:00 Greedy combinatorial auction node 1 …. node 4 available Rolling Window sold d=3 d=2 d=2 d=4 Bids n=2 n=3 n=4 n=3 v: value n: # nodes d: hours v=27 v/nd = 3 v=16 v/nd=2 v=12 v/nd=1.5 v=6 v/nd=1

  8. 1:00 3:00 4:00 5:00 2:00 2:00 4:00 5:00 6:00 3:00 Greedy combinatorial auction node 1 …. node 4 X X X X WIN v: value n: # nodes d: hours v/nd=3 v/nd=2 v/nd=1.5 v/nd=1 high low

  9. Virtual currency policy • Users don’t contribute / pay to use Mirage • User account: • Baseline amount b (e.g. 1,000 credits) • Proportional-share s (e.g. 5%) • Revenue reallocation • Redistributed to all accounts proportionally • Savings tax (“use it or lose it”) • Tax “wealthy” accounts and redistribute to “poor” ones

  10. “Markets don’t work”

  11. People do use Mirage… Over 300 bids, 300,000 node hours over 4 months

  12. Resource contention SIGCOMM SenSys

  13. Wide range of valuations

  14. Increasing values during contention SenSys SIGCOMM

  15. “Gaming isn’t a problem”

  16. S1: Underbidding • Cause: allowed bidders to see outstanding bids • During underutilization periods, users bid less than recent value (e.g. 10,10,1) • Result: lower efficiency • Counter: use sealed-bid auction

  17. S2: Iterative bidding • Cause: allowed bidders to modify bid values • Usability overhead matters • Most modified once only, understating • Result: increased complexity • Counter: bid only once

  18. v = 8 v = 4 (T) v = 4 (T+1) X X v/nd = 1 v/nd = 1 v/nd = 1 S3: Rolling window attack Bid Horizon: bids cannot start later then here Hmm... v = 32 v = 16 X X X WIN v/nd = 2 v/nd = 1

  19. v = 32 v = 8 v = 16 X X WIN v/nd = 2 v/nd = 1 v/nd = 1 S3: Rolling window attack

  20. S4: Sandwich attack Hmm... v = 48 v = 16 v = 32 v = 29 v = 12 X X WIN WIN v/nd = 1.8 v/nd = 1 v/nd = 4 v/nd = 3 v/nd = 2

  21. Conclusion • Markets • Users seem to respond to markets approach • Gaming • Users know what’s going on • Hurts efficiency and adds complexity • Deploying an online strategyproof mechanism • We need more deployments

  22. Sites • Mirage • Google: “Mirage Intel Berkeley” • http://mirage.berkeley.intel-research.com • Other group papers • http://www.chaki.com

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