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.

1

( )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