Submission doc.: IEEE 11-14/0866r0 July 2014 Johan Söder, Ericsson ABSlide 1 Traffic modeling and...
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Submission doc.: IEEE 11-14/0866r0 July 2014 Johan Söder, Ericsson AB Slide 1 Traffic modeling and system capacity performance measure Date: 2014-07-14 Authors: N am e A ffiliations A ddress Phone em ail Johan Söder Ericsson A B Färögatan 6, Stockholm , Sw eden +46 722449170 johan.soder @ericsson.com Filip M estanov Ericsson A B Färögatan 6, Stockholm , Sw eden +46 725 298 161 filip.mestanov @ericsson.com LeifW ilhelmsson Ericsson A B leif.r.wilhelm sson @ericsson.com H akan Persson Ericsson A B hakan.z.persson @ericsson.com Sean Coffey Realtek coffey @realtek.com
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Transcript of Submission doc.: IEEE 11-14/0866r0 July 2014 Johan Söder, Ericsson ABSlide 1 Traffic modeling and...
Submission
doc.: IEEE 11-14/0866r0July 2014
Johan Söder, Ericsson ABSlide 1
Traffic modeling and system capacity performance measure
Date: 2014-07-14
Name Affiliations Address Phone email Johan Söder Ericsson AB Färögatan 6, Stockholm,
Sweden +46 722449170 johan.soder
@ericsson.com Filip Mestanov Ericsson AB Färögatan 6, Stockholm,
Sweden +46 725 298 161 filip.mestanov
@ericsson.com Leif Wilhelmsson Ericsson AB leif.r.wilhelmsson
@ericsson.com Hakan Persson Ericsson AB hakan.z.persson
@ericsson.com Sean Coffey Realtek coffey
@realtek.com
Authors:
Submission
doc.: IEEE 11-14/0866r0July 2014
Johan Söder, Ericsson ABSlide 2
Abstract
In this presentation we present a simple traffic modelling method as well as system capacity evaluation methodology
Submission
doc.: IEEE 11-14/0866r0
Traffic model: File transfer & Web browsing
• STA positions from the simulation scenario document [1] are considered as tentative STA locations, i.e., STAs are not connected/active all the time, just when they have data in the buffer
• Files arrive independently in the buffers of the STAs(UL) and the APs (DL, files labelled with a receiver STA)
• Arrival process is a Poisson process
• Arrival intensity of DL and UL files has ratio, e.g, 80/20 (parameter to be agreed on)
• Different system loads are modelled by varying arrival intensity, the file size is kept constant
• Sample file size is 1MB
Slide 3 Johan Söder, Ericsson AB
July 2014
Submission
doc.: IEEE 11-14/0866r0
Traffic model: Video streaming
• Similar approach may be applied for video streaming traffic
• Randomly select which users are streaming the video
• Introduce the packets in the buffer regularly instead of randomly (i.e., CBR)
• The load will be determined by how many users are doing streaming
Slide 4 Johan Söder, Ericsson AB
July 2014
Submission
doc.: IEEE 11-14/0866r0
System capacity evaluation:Definitions
• Packet throughput = packet size / packet delay
• Packet delay = time from packet arrives in buffer until time the last ACK is received
• User throughput = average of packet throughputs for a user
• Served traffic = Sum of all successfully received packets / simulation time
• Served traffic ~ system arrival intensity * packet size
Slide 5 Johan Söder, Ericsson AB
July 2014
Submission
doc.: IEEE 11-14/0866r0
System capacity evaluation:Delay terminology
• The packet delay can be further divided into:• Queuing time – waiting while someone else uses the medium
• Contention time – backoff and deferrals
• Transmission time – transmitting
• Collision time – transmission time for failed transmissions
Dataarrives
Backoffexpires
Backoffexpires
Collision
Queuingtime
Contentiontime
Transmissiontime
Collisiontime
July 2014
Johan Söder, Ericsson ABSlide 6
Submission
doc.: IEEE 11-14/0866r0
System capacity evaluation:Example
• Consider 1 AP
• Arrival intensity 1 packet / second
• Packet size 1MByte = 8Mbit
• AP load is 8Mbps
• During 100s there will on average be 100 packets
• These will all have different packet throughput
• Assume the average packet throughput is 40 Mbps
• average delay is 0.2s 80s out of 100s there are no ongoing transmissions in the AP
Slide 7 Johan Söder, Ericsson AB
July 2014
8 Mbit
Packet tpt
1/4 s.
32 Mbps
3/4 s.
8 Mbit
64 Mbps
1/8 s.
P1
P2
1 s.
8 Mbit
P3
8 Mbit
P100
100 s.
Served traffic volume = 100 packets x 8Mbit = 800Mbit
Served traffic load = 800Mbit/100s. = 8Mbps
Submission
doc.: IEEE 11-14/0866r0
0 5 10 15 20 250
20
40
60
80
100
120
140
Served traffic per AP (DL+UL) [Mbps]
Fif
th P
erc
en
tile
Us
er
Th
rou
gh
pu
t [M
bp
s]
Ref
System capacity evaluation:Example graph
Slide 8 Johan Söder, Ericsson AB
July 2014
Increased file arrival intensity
Decreased user experience
Submission
doc.: IEEE 11-14/0866r0
System capacity evaluation:Performance measurements
• As system load (traffic intensity) increases, the delay times in accessing the channel, and the interference probability, will increase lower user throughput
• We define the system capacity as the maximum load the system can handle, while still providing sufficient performance
• The “sufficient performance” criterion may be defined as “95% of the time, the users should experience throughput above 20 Mbps”, i.e., 5th percentile throughput > 20 Mbps
Slide 9 Johan Söder, Ericsson AB
July 2014
Submission
doc.: IEEE 11-14/0866r0
0 5 10 15 20 250
20
40
60
80
100
120
140
Served traffic per AP (DL+UL) [Mbps]
Fif
th P
erc
en
tile
Us
er
Th
rou
gh
pu
t [M
bp
s]
Ref
System capacity evaluation:Sample performance
Slide 10 Johan Söder, Ericsson AB
July 2014
Performance requirement (e.g., 20Mbps)
System capacity: 13 Mbps/AP
Submission
doc.: IEEE 11-14/0866r0July 2014
Johan Söder, Ericsson ABSlide 11
Conclusion
• Traffic modeling is not related to how many STAs per BSS there are, but rather how much traffic load there is in a certain scenario (i.e., certain area)
• System capacity should be measured by the amount of traffic that the system can handle, maintaining a certain level of user experience
• Proposals:• Model file transfer, web browsing and video streaming using the
proposed method
• Evaluate system capacity using the proposed methodology
Submission
doc.: IEEE 11-14/0866r0July 2014
Johan Söder, Ericsson ABSlide 12
References
[1] 11-14-0621-04-00ax-simulation-scenarios
