Evaluation of Information Service Architectures for Grid

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Evaluation of Information Service Architectures
for Grid
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MDS-4 and DHT

• Hyerarchical architecure
• Flat architecture
• Created for different uses

3
Focus

• Information systems for grid
• Metadata resources users
• Churn
• Pragmatical approach

4
Constraints

• Fixed schema
• Multi-attribute query
• Range query
• 3 attributes

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Index list search

• The list is long
• The items are geographically dispersed

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Hierarchy, MDS4

• Bottleneck for performance
• Collected,cached,leased data.
• slow data flow, - old data

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Peer-to-peer, Multi Chord

• good for large number of keys
• - Churn

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Experiment

• Size (nodes, items) EGEE 250 ,25000
• Schema CPU,RAM,Diskst
  Group,Role,Capability
• Selectivity on whole range

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TTF,TTR skewed, ? 0.1, 250 nodes, 120
minutes,CPU data
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Std. Dev.
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TTF skewed,TTR fixed, ? 0.1, 250 nodes, 120
minutes,CPU data
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TTF skewed,TTR fixed, Membership data
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VOMS vs CPU data
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Conclusions

• MDS4, ram, slow, churnlt5min,
• Much better than Chord on skewed data
• Chord multi
• Fast
• Returns fewer keys

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Future

• More info available on Dynamic Behaviour of
  nodes?
• Increase size? / Distributed simulation platform
• Data models
• Query composition selectivity and bias
• How coul make analysis useful to cloud /hibryd
  solutions?
• Any other middleware to compare?
• Relevant for DHT ?

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Thank you for being here!
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Environment of the experiment
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Schema - CPU processor data
Attribute Unit Type Distribution Avg. Range min - max
CPU MHz integer Skewed 2000
RAM MB integer uniform 100-300
Disk Storage GB integer uniform 400-1000
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Schema membership data
Attribute Unit Type Distribution Avg. Range min - max
Group ID integer uniform NA 1-20
Role ID integer uniform NA 1-20
Capability ID integer uniform NA 1-20