Evaluation of Information Service Architectures for Grid.
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Transcript of Evaluation of Information Service Architectures for Grid.
![Page 1: Evaluation of Information Service Architectures for Grid.](https://reader036.fdocuments.in/reader036/viewer/2022070414/5697c0191a28abf838ccea4a/html5/thumbnails/1.jpg)
Evaluation of Information Service Architectures for Grid
![Page 2: Evaluation of Information Service Architectures for Grid.](https://reader036.fdocuments.in/reader036/viewer/2022070414/5697c0191a28abf838ccea4a/html5/thumbnails/2.jpg)
MDS-4 and DHT
• Hyerarchical architecure
• Flat architecture
• Created for different uses
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Focus
• Information systems for grid• Metadata: resources + users• Churn• Pragmatical approach
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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
![Page 8: Evaluation of Information Service Architectures for Grid.](https://reader036.fdocuments.in/reader036/viewer/2022070414/5697c0191a28abf838ccea4a/html5/thumbnails/8.jpg)
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, ρ= 0.1, 250 nodes, 120 minutes,CPU data
,00
20,00
40,00
60,00
80,00
100,00
120,00
1/MTTF
Neg
ativ
e ra
te
MDS4
p2p
MDS4 43,87 37,84 49,61 62,48 59,67 89,48 70,49
p2p 23,78 45,90 75,00 63,00 73,00 73,00 96,30
0,016 0,002 0,025 0,033 0,050 0,100 0,500
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Std. Dev.
0,00
20,00
40,00
samples
SD SD MDS4
SD p2p
SDMDS4
0,20 2,38 15,00 0,80 1,70 15,00 0,50
SD p2p 25,0019,0013,00 4,70 11,0032,00 1,29
1 2 3 4 5 6 7
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TTF skewed,TTR fixed, ρ= 0.1, 250 nodes, 120 minutes,CPU data
,00
20,00
40,00
60,00
80,00
100,00
1/MTTF
Neg
ativ
e ra
te
MDS4
p2p
MDS4 41,00 47,00 50,00 58,00 62,00 68,00 70,00
p2p 46,00 32,00 58,00 63,00 65,00 92,00 68,36
0,016 0,002 0,025 0,033 0,050 0,100 0,500
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TTF skewed,TTR fixed, Membership data
,00
10,00
20,00
30,00
40,00
50,00
60,00
70,00
80,00
90,00
1/MTTF
Neg
ativ
e ra
te
MDS4
p2p
MDS4 43,00 45,00 50,00 59,00 74,00 70,00 71,00
p2p 40 36 37 56 78 74 83
0,016 0,002 0,025 0,033 0,050 0,100 0,500
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VOMS vs CPU dataChord: voms vs cpu
0
20
40
60
80
100
1/TTF
nega
tive
rate
p2p_voms
p2p_cpu 46,00 32,00
p2p_voms 40 36 37 56 78 74 83
p2p_cpu 46,0032,00
46,00 32,00 58,00 63,00 65,00 92,00 68,36
1/TTF
MDS4: voms vs cpu
,00
20,00
40,00
60,00
80,00
1/TTF
nega
tive
rate
gt4_voms 43,00 45,00
gt4_cpu 41,00 47,00
gt4_voms 43,0045,00
43,00 45,00 50,00 59,00 74,00 70,00 71,00
gt4_cpu 41,0047,00
41,00 47,00 50,00 58,00 62,00 68,00 70,00
1/TTF
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Conclusions
• MDS4, ram, slow, churn<5min,
• 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