performance investigation and comparison between...
TRANSCRIPT
![Page 1: Performance investigation and comparison between …free.eol.cn/edu_net/edudown/cans2015/cans2015pdf/2201/1...virtual network • In idle traffic case, the deviation: 0.23%(single-thread](https://reader034.vdocuments.us/reader034/viewer/2022042605/5f4fa594f0c5067ff828151f/html5/thumbnails/1.jpg)
Performance investigation and comparison
between virtual networks and physical networks
based on Sea-Cloud Innovation Environment
Website: http://scie.ac.cn E-mail: [email protected]
CANS 2015, Chengdu, Sep 21, 2015
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2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Performance investigation
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Background
• Sea-Cloud Innovation Environment, a national wide
testbed supported by the “Strategic Priority
Research Program - New Information and
Communication Technology”(SPRP-NICT) of the
Chinese Academy of Sciences, is aiming to build
an open, general-purpose, federated and large-
scale shared experimental facility to foster the
emergence of new ICT.
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Background
•Providing shared and sliceable experimental facilities for academia and
industry to bridge the gap between visionary research and large-scale
experimentation.
•Establishing and practicing the methodology of experimentally -driven
innovation for the clean-slate architecture of ICT.
•Evaluating and validating new protocols, devices and research
achievements of SPRP-NICT.
Objective
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2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Experimentation
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Architecture
Experiment Topology Requests • SCIE portal
• Scie.ac.cn
• Resource control
framework
• Experiment
measurement
system
• SDN/VLAN-based
network slicing
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2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Performance investigation
![Page 8: Performance investigation and comparison between …free.eol.cn/edu_net/edudown/cans2015/cans2015pdf/2201/1...virtual network • In idle traffic case, the deviation: 0.23%(single-thread](https://reader034.vdocuments.us/reader034/viewer/2022042605/5f4fa594f0c5067ff828151f/html5/thumbnails/8.jpg)
Software--Overview
SCIE Portal
Control Center
Resource Site
Experiment
Measurement
System
Resource
Management &
Control System
Topology
Editor
Experiment
Playground
Resource
Management
Authorization
& Accounting
Site manager
Resource
Control
module
Measurement
Module Site manager…….
Experiment Service System
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SoftwareSCIE Resource Control Architecture
• Distributed resource control framework with one control center and many site managers
• Defining resource control interfaces, measurement interfaces to integrate different resource
• Light-weight VM management tool
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SoftwareSCIE measurement System
• External VM
measurement without
any plug-in in VMs
• AMQP based control
message &
measurement data
transfer
• sFlow based network
traffic measurement
• MongoDB as Storage
Engine
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SoftwareExperiment Service System
• Experiment life cycle Management
• Java & Python based experiment control library
• Topology and experiment process visualization
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Hardware
Smart-Flow Switch
• OpenFlow 1.2
• GRE tunnel
• QoS supported
• 24*GE
• 1*10GE
• Four slots
• Line Card & UTM Card
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Hardware
SCIE Rack
•Integrated network,
computing and storage
• Built-in site management
module
• Virtualization
• Dynamic scheduling
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2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Performance investigation
![Page 15: Performance investigation and comparison between …free.eol.cn/edu_net/edudown/cans2015/cans2015pdf/2201/1...virtual network • In idle traffic case, the deviation: 0.23%(single-thread](https://reader034.vdocuments.us/reader034/viewer/2022042605/5f4fa594f0c5067ff828151f/html5/thumbnails/15.jpg)
Deployment
•Four contries&Seven cities &22 sites
•Data plane via GRE tunnel; Control plane via L3 network
•2234 cores, 1510TB storage, 512TB experimental data
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2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Performance investigation
![Page 17: Performance investigation and comparison between …free.eol.cn/edu_net/edudown/cans2015/cans2015pdf/2201/1...virtual network • In idle traffic case, the deviation: 0.23%(single-thread](https://reader034.vdocuments.us/reader034/viewer/2022042605/5f4fa594f0c5067ff828151f/html5/thumbnails/17.jpg)
2015/9/28
Outline
• Background
• Architecture
• Software & Hardware
• Deployment
• Demonstration
• Performance investigation
![Page 18: Performance investigation and comparison between …free.eol.cn/edu_net/edudown/cans2015/cans2015pdf/2201/1...virtual network • In idle traffic case, the deviation: 0.23%(single-thread](https://reader034.vdocuments.us/reader034/viewer/2022042605/5f4fa594f0c5067ff828151f/html5/thumbnails/18.jpg)
• Performance investigation and
comparison between virtual
networks and physical networks
based on an advanced testbed
network
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Deployment
• Three cities & 4 sites
• VM based on KVM
• Data transmission via GRE tunnel built
based on OVS
GRE Tunnel
VM1
VM8
VM2
...
VM1
VM8
VM2
...
Beijing, China
Beijing, China
Xinjiang, China
Michigan, US
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Deployment
• Scenario– single-thread vs. multi-thread
• For each scenario
– the intra-domain case, from Beijing to Xinjiang in China
– the inter-domain case, from Beijing in China to Michigan in US
• Extensive performance evaluation tests
– UDP and TCP traffic in idle and non-idle period
• Key performance metrics– For UDP traffic
• round trip time (RTT), throughput, packet loss, and jitter
– For TCP traffic
• RTT and throughput
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Experimental results and analysis
• UDP traffic
– throughput0
10
20
30
40
50
60
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Thro
ugh
pu
t (M
bit
s/se
con
d)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
10
20
30
40
50
60
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Thro
ugh
pu
t (M
bit
/s)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
2
3
4
5
6
7
8
9
10
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Thro
ugh
pu
t (M
bit
/sec
on
d)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
2
3
4
5
6
7
8
9
10
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Thro
ugh
pu
t (M
bit
/sec
on
d)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
(a) UDP Bandwidth BJ-XJ (Idle) (b) UDP Bandwidth BJ-XJ (Non-Idle)
(c) UDP Bandwidth BJ-MI (Idle) (d) UDP Bandwidth BJ-MI (Non-Idle)
• The virtual network is very similar to single-thread physical network very similar to single-thread physical network scheme in intra-domain
and in inter-domain
the deviation less than 0.35% in intra-domain
about 0.21% in inter-domain
• The deviation is stable (multi-thread virtual network vs. single-thread
physical network)
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Experimental results and analysis
• UDP traffic
– packet loss rate(a) UDP Packet Loss BJ-XJ (Idle) (b) UDP Packet Loss BJ-XJ (Non-Idle)
(c) UDP Packet Loss BJ-MI (Idle) (d) UDP Packet Loss BJ-MI (Non-Idle)
• Single-thread virtual network and single-thread physical network are
better than multi-thread virtual network scheme in all cases
• The deviation is less than 1% (multi-thread virtual network vs. single-
thread physical network) 0.17% in intra-domain
about 0.23% in inter-domain
0
5
10
15
20
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Pa
cket
Lo
st R
ate
(%
)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
5
10
15
20
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Pa
cket
Lo
st R
ate
(%
)
Seconds
VM(singel-thread,non-Idle)
PHY(singel-thread,non-Idle)
VM(multi-thread,non-Idle)
0
5
10
15
20
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Pac
kets
Lo
st R
ate
(%)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
5
10
15
20
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Pack
ets
Lost
Rat
e (%
)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
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Experimental results and analysis
• UDP traffic
– jitter (a) UDP Jitter BJ-XJ (Idle) (b) UDP Jitter BJ-XJ (Non-Idle)
(c) UDP Jitter BJ-MI (Idle) (d) UDP Jitter BJ-MI (Non-Idle)
• The jitter of inter-domain environment was higher than that of intra-
domain environment with about 13.5%
• Jitter in Multi-thread virtual network is higher than single-thread physical
network 2.6% higher in intra-domain environment
10.2 % higher in inter-domain environment
• The distance is the main factor affecting the jitter
0
0.2
0.4
0.6
0.8
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Jitt
er (
ms)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
0.2
0.4
0.6
0.8
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Jitt
er (
ms)
Seconds
VM(single-thread,non-Idle)PHY(single-thread, non-Idle)VM(multi-thread, non-Idle)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Jitt
er (
ms)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
Jitt
er (
ms)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
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Experimental results and analysis
• UDP traffic
– RTT(a) a UDP RTT BJ-XJ (Idle) (b) UDP RTT BJ-XJ (Non-Idle)
(c) UDP RTT BJ-MI (Idle) (d) UDP RTT BJ-MI (Non-Idle)
• Single-thread physical network is more stable and smaller than
single-thread and multi-thread virtual network • RTT is most stable and lowest in all cases in single-thread physical network
• The RTT of single-thread physical network is about 3.3% smaller than single-
thread and multi-thread virtual network schemes
• The RTT is not so stable in non-idle scenario, the deviation between
idle and non-idle cases is 0.1%
• The background traffic is the key influence factor of RTT and the
performance of network experiment in virtual network environment
50
55
60
65
70
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
50
55
60
65
70
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
200
210
220
230
240
250
260
270
280
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
200
220
240
260
280
300
320
340
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
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Experimental results and analysis
• TCP traffic
– throughput(a) TCP Throughput BJ-XJ (Idle) (b) TCP Throughput BJ-XJ (Non-Idle)
(c) TCP Throughput BJ-MI (Idle) (d) TCP Throughput BJ-MI (Non-Idle)
• Throughput in Idle case is better than non-idle case
• Throughput in intra-domain environment is higher than that in inter-
domain environment
• After slow start, the throughput of single-thread physical network is
higher than that of single-thread and multi-thread virtual network
scheme
• The throughput of single-thread virtual network is the most stable and
is very similar to single-thread physical network in non-idle case
0
50
100
150
200
250
300
1 11 21 31 41 51
Thro
ugh
pu
t (M
bit
/sec
on
d)
Samples
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
50
100
150
200
250
300
1 11 21 31 41 51
Thro
ugh
pu
t (M
bit
/sec
on
d)
Samples
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
0
20
40
60
80
100
1 11 21 31 41 51
Thro
ugh
pu
t (M
bit
/sec
on
d)
Samples
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
0
20
40
60
80
100
1 11 21 31 41 51
Thro
ugh
pu
t (M
bit
/sec
on
d
Samples
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
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Experimental results and analysis
• TCP traffic
– RTT(a) TCP RTT BJ-XJ (Idle) (b) TCP RTT BJ-XJ (Non-Idle)
(c) TCP RTT BJ-MI (Idle) (d) TCP RTT BJ-MI (Non-Idle)
• Stability of RTT single-thread physical network > single-thread virtual network > multi-thread
virtual network
• In idle traffic case, the deviation: 0.23%(single-thread physical network vs. single-thread virtual network)
0.55%(single-thread physical network vs. multi-thread virtual network)
• In non-idle traffic case, the deviation: 3.7% (single-thread physical network vs. single-thread virtual network)
4.5% (single-thread physical network vs. multi-thread virtual network)
50
52
54
56
58
60
62
64
66
68
70
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
50
52
54
56
58
60
62
64
66
68
70
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
220
230
240
250
260
270
280
290
300
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,Idle)
PHY(single-thread,Idle)
VM(multi-thread,Idle)
220
230
240
250
260
270
280
290
300
1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341
RTT
(m
s)
Seconds
VM(single-thread,non-Idle)
PHY(single-thread,non-Idle)
VM(multi-thread,non-Idle)
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Experimental results and analysis
• Conclusion• 1) the RTT and jitter of virtual networks have little deviation
from physical networks,
• 2) the throughput and packet loss rate of virtual networks are
similar to physical networks,
• 3) the performance of single-thread virtual network is more
similar to the existing physical network than the multi-thread
virtual networks,
• 4) the multi-thread virtual networks have certain deviation from
physical networks, but the deviation is stable and shows
certain characteristics.
• Thus, it is possible to get the performance
of real physical networks in virtual
networks
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