on maximum stability with enhanced scalability in high-churn dht deployment junfeng xie, nanjing...
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A relaxation Vienna – so many famous places of interest ICPP – so few audience 3TRANSCRIPT
On Maximum Stability with Enhanced Scalability in High-Churn
DHT Deployment
Junfeng Xie, Nanjing University, ChinaZhenhua Li, Peking University, China
Guihai Chen, Nanjing University, ChinaJie Wu, Florida Atlantic University, USA
Outline
• A relaxation• Motivation• Related work• Grouping Strategy• Maximum Stability Problem• Performance Evaluation• Conclusion and Future Work
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A relaxation
• Vienna – so many famous places of interest • ICPP – so few audience
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A relaxation (cont.)
• Our paper has many formula• Steven Hawking: “One more formula, one half
audience”• So I add more pictures, reduce formula
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Motivation
• P2P, DHT – hot topics in the past 10 years• Why? – Utilization of Internet edge nodes
Internet edge nodes• Advantages: enormous – many many … so
scalability• Disadvantages: dynamic – join leave … so
stability5
Motivation (cont.)
• A fundamental problem of P2P and DHT-- efficient leverage of dynamic nodes (dwarfs)
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Related Work
• GiantOnly – OpenDHT : giants as DHT servers, dwarfs as clients
• Giant ≈ Dwarf – Chord, Pastry, Tapestry, Kademila, Cycloid
a giant = a DHT node, a dwarf = a DHT node
Problem? scalability vs. stability
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Grouping Strategy• Idea: 1) a giant = a DHT node 2) a group of dwarfs = a DHT node
• Inter-group: DHT• Intra-group: random,erasure-code or replicate
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Grouping Strategy (cont.)
• Grouping Strategy’s advantages:1)Enhanced scalability -- near Giant ≈ Dwarf2)Maximum stability -- near GiantOnlySweet spot between GiantOnly and Giant ≈ Dwarf
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Grouping Strategy (cont.)
• A simple example
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Grouping Strategy (cont.)
• Kernel problem: 1) how many groups? – N/logN2) how to group? – next section
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Maximum Stability Problem
• MSG problemto minimize
• And
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Maximum Stability Problem (cont.)
• 1) MSG problem is NP-hard (omitted here)• 2) MSG problem is infeasible – requires each
node’s join and leave time
• So restricted MSG problem 1) homogeneous grouping – nodes within the
similar dynamics are grouped 2) stochastic computation of ψ, σ and Var(ψ).
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Maximum Stability Problem (cont.)
• Homogeneous grouping
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ky0y 1y 2y 3y
Session length time (stl) intervals:
so Var(ψ) only depends on (y1, y2, …, yk, …)
ky0y 1y 2y 3y
Assume the nodes’ join and leave form a predictable stochastic process
Session length time (stl) intervals:
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Maximum Stability Problem (cont.)
Maximum Stability Problem (cont.)
• Therefore, the restricted MSG problem is in fact: how to design the intervals (y1, y2, …, ym-
1) so as to minimize Var(ψ)? -- Solution: Matlab function fminsearch(Var, y1, y2, …)
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Performance Evaluation
• Grouping snapshot (sorted by stl intervals)
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Performance Evaluation (cont.)
• Stability (churn rate)
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Performance Evaluation (cont.)
• Scalability (storage capacity)
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Conclusion and Future Work
• Conclusion: A homogeneous grouping strategy, which can
achieve maximum stability and enhanced scalability
• Problems: 1) Heterogeneous grouping? 2) Fast optimization algorithm
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The End
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