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A performance vs. cost framework for evaluating DHT design tradeoffs under churn

A performance vs. cost framework for evaluating DHT design tradeoffs under churn. Jinyang Li, Jeremy Stribling , Robert Morris, Frans Kaashoek, Thomer Gil MIT Computer Science and Artificial Intelligence Laboratory. Distributed Hash Tables. Applications:.

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A performance vs. cost framework for evaluating DHT design tradeoffs under churn

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  1. A performance vs. cost framework for evaluating DHT design tradeoffs under churn Jinyang Li, Jeremy Stribling, Robert Morris, Frans Kaashoek, Thomer Gil MIT Computer Science and Artificial Intelligence Laboratory

  2. Distributed Hash Tables Applications: Coral, OpenDHT, UsenetDHT, ePost, OceanStore, CoDNS, Overnet IP Address DHT Lookup Layer: Chord, Tapestry, Bamboo, Kademlia, Pastry, Kelips, OneHop

  3. Static DHT Comparison DHT Hop Count Table Size Static performance metrics don’t reflect cost

  4. Goal: Compare DHTs Under Churn • Protocols differ in efficiency of their mechanisms • Example mechanism: Extra state • Reduce hop count • Increased table maintenance bandwidth • PVC: A performance vs. cost framework • Performance: median lookup latency • Cost: average bandwidth consumed / node

  5. Why Is Comparing DHTs Hard? • Protocols have lots of parameters: • Routing table size • Refresh interval • Parallelism degree • How do we ensure a fair comparison?

  6. 271 261 255 250 240 14 18 21 10 23 Parameters Affect Comparison Tapestry Download, run Chord Download, run Tapestry Increase Chord table size Increase Tapestry table size Increase Chord refresh rate Chord Median lookup latency 0 Bandwidth consumed

  7. PVC Parameter Exploration Chord Median lookup latency Bandwidth consumed • Convex hull outlines the most efficient tradeoffs

  8. Comparing DHTs with PVC Chord Tapestry Median lookup latency Bandwidth consumed

  9. Implementation protocol p2psim topology workload PVC results

  10. Experimental Setup • Chord, Tapestry, Kademlia, Kelips, OneHop • Use measured topology of DNS servers [Gummadi et al., IMW ’02] • 1,024 nodes • Median RTT: 156 ms • Workload: • Each node joins/crashes with mean of 1 hour • Each node issues lookups with mean of 10 min

  11. DHT Comparison Median lookup latency (msec) Bandwidth consumed (bytes/node/sec)

  12. DHT Mechanisms and Parameters • How can we use PVC to study mechanisms? • Observation: Parameters control mechanisms • Extra state  table size parameter • Table freshness  refresh interval

  13. PVC Parameter Convex Hulls Chord Median lookup latency (msec) Bandwidth consumed (bytes/node/sec)

  14. Extra State Is More Efficient than Maintaining Freshness Chord Refresh Interval Table Size Median lookup latency (msec) Bandwidth consumed (bytes/node/sec)

  15. Parallel Lookup Is More Efficient than Maintaining Freshness Kademlia Refresh Interval Parallelism Median lookup latency (msec) Refresh more Refresh Less Bandwidth consumed (bytes/node/sec)

  16. DHT Design Insights with PVC

  17. Related Work • Protocols designed for churn: • Bamboo [Rhea et al., USENIX ’04] • MSPastry [Castro et al., DSN ‘04] • Churn theory: • Statistical theory of Chord under churn [Krishnamurthy et al., IPTPS ’05] • Chord half-life [Liben-Nowell et al., PODC ‘02] • Churn metrics: • K-consistency [Lam and Liu, SIGMETRICS ’04]

  18. Summary/Future Work • A unified performance/cost framework for DHT evaluation (PVC) • We used the lessons from our PVC-based study to design Accordion[Li et al., NSDI ’05] • One parameter: bandwidth • Self-tunes all others http://pdos.csail.mit.edu/p2psim

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