grid simulation (alien) network data transfer model eugen mudnić technical university split -fesb
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Grid simulation (AliEn)
Network data transfer model
Eugen MudnićTechnical university Split -FESB
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Outline AliEn simulation - AliEnSim Network data transfer model for the
Grid simulation model description model accuracy & performance
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AliEnSim GRID simulation Discrete Event simulation (DES) Simulates AliEn (like) grid data
processing/storage It can be used for:
planning of resource requirements (network, storage, CPU)
identifying system bottlenecks testing system scalability ...
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AliEnSim
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AliEnSim
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AliEnSim
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AliEnSim
low efficiency (large RTT & congestion)
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Network data transfer model Packet based (ns-2) – accurate, slow for
grid simulation, many configuration parameters
Fluid based – faster but not satisfactory for the grid simulation, many configuration parameters
Approximate-coarse grained model ? Requirements:
fast (at least two orders of magnitude faster than ns-2) minimal number of parameters -> assumption of
properly configured network satisfactory accurate for the grid simulator -> exhibits
most important network limitations
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Very simple model
Network as a set of links shared by
changeable number of data
streams
CE1
SE1
SE2
SE3
100MB/s
30MB/s
50MB/s
30 MB/s
1GB/s
1GB/s
100MB/s
LAN1LAN2
LAN3
links with capacity ( C1,..CL )
N streams , every stream has a predefined transfer route ri {1,…,L}
Every stream has equal priority
Stream bandwidth allocation must conform to:
( )i
i lr l
x C
Stream instantaneously allocate available capacity
10
10-3
10-2
10-1
100
101
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
time[s]
MB
it/s
0.6ms
1.4ms
2.8ms
4.0ms
5.4ms
16.4ms
60.4ms
200.4ms
TCP stream cannot instantaneously allocate available capacity
TCP bandwith allocation (BIC)
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AGNS- approximate grid network simulation
CE1 SE2
SE3
200MB/s RTT=50ms
200MB/sRTT=5ms
1GB/s
1GB/s
100MB/s
LAN1LAN2
LAN3
more complicated
bandwith allocation
alghoritm (not described here)
•includes TCP unfairness efect
•includes TCP bandwith allocation dynamic (startup phase)
bottleneck
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AGNS- slow start approximation Startup phase will be simulated as:
delayed start of file transfer limited bandwidth allocation for a small files
TCP fairness : data flow allocated bandwidth is a function of streams RTT at the time of data flow start
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a) Complete transfer is finished during startup phase
Data flow can reach only reduced bandwidth allocation Φsli.
00
MB
it/s
time[s]
S
dss
Φi
ts
Φsli
Di = file size
sl
Dtd i
slss
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b) Partial transfer during startup phase
0
time[s]
Thp
[MB
it/s]
S
dss
Φi
ts
i
Dtd i
sss
where D’i is number of
bytes transferred until time
ts
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AGNS- approximative grid network simulation
• relative aggregate performance metrics will be maintained by data flow bandwidth allocation as a function of its RTT ratio to other concurrent data flows RTT
state of the simulator is calculated only 3-times for each transfer !!!
Results of AGNS are compared to Ns-2 simulation at aggregate level.
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( )K
n
i NLi
x Bu
1
11i u n
fi f
jj
BRTT
RTT
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Network test topology & performance
n1
1GBps&
10GBps/0.4ms
ftp
TCP
Datasink
nbn2
n4
10GBps/10ms na
n3
CE1
ftp
TCPCE2
ftp
TCPCE3
ftp
TCPCE4
Bottleneck link
ns-2 AGNS
400files/91GByte/1GBps
1320 s 0.37 s
3800files/853GByte/10GBps
6180 s 1.74 s
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1GB bottleneck
0
50
100
150
200
250
300
350
400
450
500
0 50 100 150 200 250 300 350 400
samples
time[
s]]
AGNS
Ns-2
5ms/10ms/20ms/30ms (fairness)
00:00 00:10 00:20 00:30 00:400
20
40
60
80
100
120
140
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
aggregate throughput
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00:00 00:15 00:30 00:45 01:00 01:150
10
20
30
40
50
60
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
10
20
30
40
50
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
10
20
30
40
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
10
20
30
40
50
60
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
CE1 RTT=5ms CE2 RTT=10ms
CE3 RTT=20ms CE4 RTT=30ms
throughput
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10GB bottleneck
0
20
40
60
80
100
120
140
160
0 500 1000 1500 2000 2500 3000 3500
samples
time[
s]]
AGNS
Ns-2
5ms/10ms/20ms/30ms
00:00 00:10 00:20 00:30 00:400
100
200
300
400
500
600
700
800
900
1000
1100
1200
time[h:m]
thro
ughput[
MB
/s]
AS
ns
aggregate throughput
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00:00 00:15 00:30 00:45 01:00 01:150
50
100
150
200
250
300
350
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
50
100
150
200
250
300
350
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
50
100
150
200
250
300
350
400
time[h:m]
thro
ughp
ut[M
B/s
]
AS
ns
00:00 00:15 00:30 00:45 01:00 01:150
50
100
150
200
250
300
350
400
time[h:m]
thro
ughp
ut[M
B/s
]
AGNS
ns-2
CE1 RTT=5ms CE2 RTT=10ms
CE3 RTT=20ms CE4 RTT=30ms
throughput
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simulation using AGNS model is fast it looks enough accurate to exhibit
realistic congestion effects of the network traffic
should be compared with real measurements
Conclusion
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