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© Copyright 2013 Shunra Software, LTD. Information contained herein is subject to change without notice.
Shunra University Session 1
Introduction to Network Virtualization
© Copyright 2013 Shunra Software, LTD. Information contained herein is subject to change without notice.
Let’s Begin with a Bit of Theory
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The Network Impact
3
Consider 2 Users - 1 in NY, 1 in Tokyo–Both access the same application in the NY Data Center–Will they all experience the application the same way?– If not, Why not?
TokyoLondonNew York
New YorkData Center
WAN
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Network Impairments• Conditions which inhibit the flow of
data across a network• Key Impairments are:
– Network Delay– Jitter (Delay variation, inter-packet gap
variation)– Packet Loss (inverse of delivery rate)– Bandwidth Constraints– Bandwidth Utilization
4
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The Mobile Network Impact
5
Consider 2 Mobile Users in NYC, 1 on WiFi one on 3G–Both access the same mobile application in the NY Data Center–Will they all experience the application the same way?– If not, Why not?
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Mobile Network Impairments
• Mobile Networks Experience Extreme Conditions of the Same Net Impairments– More Network Delay (Last Mile + Backhaul,
RRC latency)– More Jitter (Delay variation, inter-packet gap
variation)– More Packet Loss (inverse of delivery rate)– More Bandwidth Constraints– More Bandwidth Utilization
6
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Why is There Delay on a Terrestrial Network?
• Network Delay– Propagation Delay– Processing / Insertion /
Serialization Delay– Queueing Delay
A Bt (msec) = d / (2/3)c
Signal
d
Packet PacketPacket Packet PacketBUSY
Lost Packet
7
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New York
London
Frankfurt
Tokyo
Sydney
Signal Speed – MPLS WAN
• Distance
• TheoreticalMinimum Signal Time(One Way)
• Speed of Light = 299,792.458 km/s
New York London Frankfu
rt Tokyo Sydney
New York
5,585km
6,219km
10,871km
15,998km
London 639km 9,585km
16,991km
Frankfurt
9,357km
16,480km
Tokyo 7,793km
New York
London Frankfurt
Tokyo Sydney
New York 28ms 31ms 54ms 80ms
London 3ms 48ms 85ms
Frankfurt 47ms 82ms
Tokyo 39msT = D / (2/3)c
8
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Internet Consumer Latency
Broadband Latency (FCC)
ConnectionType
RTT
Fiber 17ms
Cable 28ms
DSL 44ms
http://www.fcc.gov/measuring-broadband-america
“Fiber-to-the-home services provided 17 ms round-trip latency on average, while cable-based services averaged 28 ms, and DSL-based services averaged 44 ms.”
9
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Mobile Latency – Last Mile + Backhaul
10
For more on this topic checkout:Ilya GrigorickMobile Performance from the Radio Up session at Google IO
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Mobile Latency – 1st. Data point
Ofcom study, UK Mobile Networks, May ‘11
http://stakeholders.ofcom.org.uk/binaries/research/telecoms-research/bbspeeds2010/Mobile_BB_performance.pdf
Static Tests:
User Panel:
“Latency… was an average of 117 milliseconds. Nearly two thirds of tests took more than 100 milliseconds”
“Average latency was 192 milliseconds and around a third of tests delivered latency of higher than 200 milliseconds”
11
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Mobile Latency – 2nd. Data point
Cisco Cloud Index, 2010-2015
“Global average fixed latency is 125 and average mobile latency is 290… Global mobile consumer average latency is 307.3 ms”
12
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Mobile Latency – Summary of Averages
13
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Packet Loss
Packets get dropped on an end to end link due to the following:–Network congestion causes queues to saturate
–Network congestion triggers RED
– Interference on wireless networks
–Hardware errors
–Firewall Policies
Packet loss is the inverse of delivery rate–100% - packet loss rate = delivery rate
Random Early DetectionAverage queue monitored size & packets dropped based on statistical probabilities. If buffer is almost empty, all incoming packets are accepted. As queue grows, probability of dropping incoming packet grows. When buffer is full, probability reaches 1 and all incoming packets are dropped.
14
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Packet LossPacket Loss, Akamai/MIT Research
Tested 149 Million connections in 51 countries– Compared PL for mobile networks from non-mobile networks
Most connections have no packet loss (Median PL is 0%).– 75th percentile usually zero too
Average connection packet loss: 2.5%– Fixed network average is 2.2%
Implies connections are usually fine, but sometimes terrible– The average PL for the non-zero half is 5%
Suggests “small” connections have higher Packet Loss– HTTP Connections are often small
http://pam2012.ftw.at/papers/PAM2012paper6.pdf
15
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Jitter
Jitter = Variability over time of latency across a networkPDV – Packet Delay VariationConstant Latency = Zero Jitter
Jitter
No Jitter
Jitter-Sensitive Applications:• Video• VoIP
16
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Bandwidth
17
Bandwidth = Network CapacityThink of number of lanes on the highwayConstraints the following:–number of user sessions * application throughput of each session
LAN Capacity
128Kbps - 5 Mbps
WAN Capacity (examples)
100 Mbps or
1 Gbps
T3 - 45 Mbps
T1 – 1.5 Mbps
Mobile Capacity (examples)
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Mobile Bandwidth in Theory
18
Protocol Max Downlink Max Uplink
GPRS 56-115 Kbps
CDMA200 (1X) 153.6 Kbps
Edge 236.8 Kbps
3G Bar 2 Mbps stationary client384 Kbps moving client
EV-DO 2.5-4.9 Mbps 0.15-1.8 Mbps
EDGE Evolution 1.6 Mbps 0.5 Mbps
HSDPA 2 Mbps 200 Kbps
HSPA+ 14.4 Mbps
4G Bar 1 Gbps stationary client100 Mbps moving client
HSPA+ Release 11 21-672 Mbps 5.8-168 Mbps
LTE 100-300 Mbps 50-75 Mbps
WiMax 37-365 Mbps 17-376 Mbps
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Mobile Bandwidth
19
You only get those speeds it if you’re this guy…
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Mobile Bandwidth
20
PCWorld/Novarum3G–Download: 0.59 – 3.84 Mbps–Upload: 0.56 – 1.44 Mbps
4G–Download: 2.81 – 9.12 Mbps–Upload: 0.97 – 5.86 Mbps
Date: Apr, 2012
Source (PCWorld): http://bit.ly/JX7MQw
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Test Time!
How much impact does the difference in Bandwidth & Latency have on web performance?
Tested Sites: Alexa US Top 100Details:–Increase Latency, Download & Upload Bandwidth separately
–Set no limits on other two variables
–Run each test 3 times, use median result
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Download BW Impact on Load Time
DSL
Cable FIBER
Poor Cell Conn
Avg Cell Conn
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Upload BW Impact on Load Time
DSL
Cable FIBER
Poor Cell Conn Avg Cell Conn
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Latency Impact on Load Time
DSL
CableFIBER
Poor Cell Conn
Avg Cell Conn
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Bandwidth/Latency Difference – Conclusions for Web Performance
Upload difference doesn’t matter much until <200 KBPS
Download difference DOES matterLatency difference matters the most
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The Impact of Performance Optimization
26
Consider the 3G Mobile User in NYC, Running 2 Mobile Banking apps–Both apps run from the same handset at the same time–Will both apps perform the same way?– If not, Why not?–Hold that thought until we get to the analysis session
© Copyright 2013 Shunra Software, LTD. Information contained herein is subject to change without notice.
Knowing all that…
How are Organizations Testing Today?
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Current Performance Testing Vs. Production
DevicesSite Type
Branch Office
Residential
Mobile (Anywhere)
NetworkData CenterFirewall
Road Warrior
28
Mobile Salesforce
WANVPN
DSL/CableWiFi
4G 3G 2.5GEtc.X X
XX
XXAutomated
Testing
Manual Testing
Load Testing
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MyAT&T Mobile App – Prod Vs. Test
WiFi Based Lab
Mobile Customers
3GLTEEdgeWiFi
AT&T Data Center
myAT&T – Dev/Test
AT&T Cloud Partner Services
WiFi based mobile tester
01-Launch_App
02-Login
03-View_Bill
04_Download_PDF
05-Usage
06-My_Plan
07-View_Line
08-Logout
02468101214
1.6
11.6
5.36.8
4.4 4.1
9.2
1.3
MyAT&T iPhone Application - Common User Actions
Wifi
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MyAT&T Mobile App – Prod Vs. Test
Mobile Customers
3GLTEEdgeWiFi
ATT Data Center
HP - Virtual Users
myAT&T – Dev/Test
AT&T Cloud Partner Services
Hi Speed Lab Network
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Mobile End User Experience Testing with Shunra
Mobile Customers
3GLTEEdgeWiFi
ATT Data Center
Shunra Mobile Virtualization
myATT – Dev/TestShunra mobile tester
AT&T Cloud Partner Services
SNV-M
www.shunra.com Network virtualization for software testing.
Mobile End User Experience Testing with Shunra
Mobile Customers
3GLTEEdgeWiFi
ATT Data Center
Shunra Mobile Virtualization
myATT – Dev/TestMobile Labs Integration
AT&T Cloud Partner Services
SNV-M