Rohan Murty Harvard University Jitendra Padhye, Ranveer Chandra, Alec Wolman, and Brian Zill Microsoft Research.
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Transcript Rohan Murty Harvard University Jitendra Padhye, Ranveer Chandra, Alec Wolman, and Brian Zill Microsoft Research.
Rohan Murty
Harvard University
Jitendra Padhye, Ranveer Chandra, Alec Wolman, and Brian Zill
Microsoft Research
1
Increased adoption and usage [Forrester]
Culture of mobility: Users tend to use Wi-Fi
even when wired connections are available
[Gartner, Forrester, Economist]
Move towards an all wireless office
Users want wire-like performance
from wireless networks
2
Corporate WLAN
Study:
12 users
< 1 Mbps each
3
Focus on coverage
Fewer APs than clients
Clients talk to APs far away; worsens rate anomaly
Clients pick APs to associate with
Use RSSI of beacon packets
Agnostic to channel load at APs
Lack adaptive behavior
No load balancing; fixed channel assignments
Congestion and hotspots worsen
4
Focus on capacity
Lots of APs; densely deployed
Clients can talk to APs near by; mitigates rate anomaly
Infrastructure picks client-AP associations
Global view of network conditions (channel load,
interference, etc.)
Adaptability
Load balance associations; Dynamic channel assignment
Redistributes load away from local hotspots
5
No client modifications
Works with legacy clients
Changes limited to the infrastructure
Easy to deploy
Self-managing
6
Interface with clients
Send summaries to DC
DenseAP Nodes (DAPs)
Commands
Summarized
Data
Wired Network
Commands to
DenseAP nodes
Associations
Channel Assignments
Load Balancing
Summarized Data
from DenseAP nodes
DenseAP Central
Controller (DC)
7
Controlling Associations
Mechanisms
Policy
Dynamic Channel Assignment
Mechanism
Policy
Load Balancing
Mechanism
Policy
8
ACL
ACL
00:09:5B:5A:1F:4F
ACL
9
Probe Request
MAC = 00:09:5B:5A:1F:4F
RSSI = 30
ACL
Probe Request
MAC = 00:09:5B:5A:1F:4F
RSSI = 42
ACL
00:09:5B:5A:1F:4F
ACL
Probe Request
MAC = 00:09:5B:5A:1F:4F
RSSI = 40
10
ACL
Probe
Response
ACL
Accept
Client
00:09:5B:5A:1F:4F
ACL
00:09:5B:5A:1F:4F
Client only sees one DAP at any given time
11
Overall goal: Associate client with a DAP
that will yield good throughput
What is the quality of a connection between a client
and a DAP? (rate)
How busy is the medium around each DAP?
12
Available
Capacity (AC)
(Mbps)
=
Expected
Transmission-Rate
(Mbps)
X
Free Air Time
(%)
13
DAP
DAP Free
Free RSSIRSSIEx.
AirAirTxTime
Time
Rate
RSSI = 10
DAP1
DAP1 0.35
0.35 20 20 18
Free air
Probe Request
DAP2
time = 0.22 DAP2
DAP2 0.22
0.22 10 10 6
DAP3 0.45
0.45 30 30 48
DAP3
Probe
Request
Probe
Response
AC
6.3
1.32
21.6
Accept
RSSI
= 30
Client
DAP3
Free air
time = 0.45
DAP1
RSSI = 20
Free air time = 0.35
14
Correlation between
RSSI of Probe Request
packets
Avg. throughput between a
DAP-client pair
Rough approximation ordering of DAPs
Online profiling method
that builds RSSI to datarate estimates
Average Throughput (Mbps)
20
18
16
14
12
10
8
6
4
2
0
Upload
0-9
Download
10 - 19 20 - 29 30 - 39
RSSI Values
40+
Upload and RSSI correlation = 0.71
Download and RSSI correlation = 0.61
15
Estimate how busy is the
medium around at a DAP
Technique similar to
ProbeGap*
Measure time taken to finish
a packet transmission
Estimates match up closely
with offered traffic load
100
Estimated Load (%)
80
60
40
20
0
0
50
Actual Load (%)
100
*Lakshminarayan et al., 2004
*Vasudevan et al., 2005
16
Integrated into the association process
DAPs not discovered by clients don’t need
channels
A DAP is assigned a channel only when it
goes from being passive (no clients) to active
(services at least one client)
Central controller assigns channel with least load
17
So far, associations when a new client joins the
network
No association is perfect
Client traffic demands change
Local hotspots created
18
Central controller monitors load on every DAP
When channel load on a DAP crosses a certain
threshold
Client causing most load is determined
Moved to less loaded DAP nearby
Ensure client continues to get at least as much available
capacity at the new DAP
Load balancing achieved via handoffs
Use association control; manipulate ACLs on DAPs
19
20
1 Corp AP
(0,0)
3026
3026
3028
3028
24 DAPs
3048
DCR
3048
3046
DESNEY
3046
3044
3044
3042
V-JWING
3042
3131
3131
3106
GREGSMI
3106
3030
3030
3153
3153
3151
3151
3116
MATTU
3116
3118
BROWN
3118
3120
SWINDER
3120
3134
STEEDLY
3134
3035
V-DOAVEL
V-JONAHA
V-TEDKAO
3035
3380
3380
3377
3377
3001
3001
3354
ZHAO
3354
3338
JELSON
3338
3336
LIUJ
3336
3334
PADMANAB
3334
3320
PADHYE
3320
3318
HELENW
3318
3371
3371
3316
SAGARWAL
3316
3314
HOWELL
3314
3312
RICHDR
3312
3181
3181
3307
DMALTZ
3307
3329
3329
3305
MZH
3305
3331
3331
3333
3333
3303
3303
3306
BZILL
3306
3300
3300
3304
JDUNAGAN
3304
3302
JGEMMELL
3302
3215
3215
3239
3239
3237
CYL
3237
UP
STR32
STR32
DN
3242
3242
3244
JFAY
3244
3246
GEORGP
3246
3248
SDRUCKER
3248
3252
WONG
3252
3180
3180
3205
3205
3161
3161
3159
3159
3325
3325
3240
3240
3203
3203
3210
3210
3235
BODHIP
3235
3230
3230
3234
V-AVD
3234
3209
3209
3217
BLINN
3217
3206
KENTOY
3206
3179
3179
3222
3222
3219
3219
3208
ANANDAN
3208
3110
3110
3138
3138
3351
3351
3308
DANSIMON
3308
3309
3309
3330
3330
3347
T-ANDRES
3347
CH33
CH33
3204
3204
3160
3160
CH32
CH32
3213
3213
3207
3207
3165
3165
3340
3340
3360
3360
3211
3211
3321
3321
3323
3323
3343
RANVEER
3343
3341
3341
3002
3002
CH31
CH31
3145
3145
3141
3141
3339
SUMANN
3339
3363
RATUL
3363
3006
3006
3021
3021
3167
3167
3163
3163
3143
3143
3136
SBKANG
3136
3356
3356
3379
3379
3005
3005
3022
3022
3149
3149
3139
T-LUCASK
3139
3114
NURIA
3114
3372
LORCH
3372
3310
3310
3201
3201
802.11 a/bg
3374
BAHL
3374
3359
JOHNDO
3359
EL 31
EL 31
3125
3125
3112
SZELISKI
3112
3376
ALECW
3376
CI32
CI32
3004
3004
3130
3130
3108
BRIANME
3108
3378
BOLOSKY
3378
3019
EMREK
3019
3037
3037
3140
3140
3123
3123
3012
SHUOCHEN
3012
EL 32
EL 32
3147
3147
3100
3100
3014
ARUNKU
3014
3040
3040
3103
3103
3104
GGR
3104
3033
3033
3039
3039
UP
3102
MARYCZ
3102
3016
CHADV
3016
3020
3020
3032
MFORNEY
3032
DN
STR31
STR31
24 Clients
3018
BRADDAN
3018
3000
3000
3034
RAMANC
3034
3052
3052
3024
YMWANG
3024
3233
3233
3232
3232
3220
3220
3154
MCOHEN
3154
3156
ERUDOLPH
3156
3172
LARRYZ
3172
3174
A-HGOOD
3174
3176
PETERJ
3176
3178
CRAIGVI
3178
3200
3200
3212
LORIMAC
3212
3214
CLOOP
3214
3216
MARCEL
3216
3218
3218
3224
HHOPPE
3224
3226
JOHNSNY
3226
3228
BGUENTER
3228
(98,32)
21
Performance
Density
Channels
Intelligent Association
Load Balancing
22
Per-Client Througput (Mbps)
20
18
16
14
12
10
8
6
4
2
0
DenseAP
Corporate
Corporate
WLAN WLAN
Gains due to
•More channels
1250% gain
•DAP density
•Intelligent associations
Why?
2
4
6
8
Number of Clients
10
12
23
Put all DAPs on the same channel
Factors out
Channels
Intelligent Associations: same load on all DAPs
Single out impact of
Density
24
Avg. Per-Client
Throughput (Mbps)
20
Corporate WLAN
DenseAP - 1 Channel
15
10
5
0
1
2
3
4
Number of Clients
5
6
Higher density provides better performance
25
Is intelligent association control necessary?
26
Client-Driven
Disable intelligent association control
Let clients pick DAP to associate with (conventional WLANs)
Compare with DenseAP
Factors out
Channels
Density
Single out impact of
Intelligent association
27
Per-Client Throughput (Mbps)
20
18
16
14
12
10
8
6
4
2
0
Client-Driven
DenseAP
160% gain
2
4
6
8
Number of Clients
10
12
Intelligent association policy is necessary
28
29
Throughput (Mbps)
25
Client 1
improves
20
15
Clients 2 & 3
improve
10
Client 1
moved
5
Client 2
moved
Client 3
Client 1
Client 2
0
0
50
100
150
Time (s)
200
250
300
30
Load balancing algorithm and mechanism
Mobility
Performance
Fewer DAPs
Fewer channels
802.11g
…..
Scalability
31
Plenty of prior work on static channel assignment, power
control and associations
Each studied each aspect in isolation
Require client modifications [Ramani and Savage, Infocom 2005]
SMARTA [Ahmed et al., CoNext 2006]
Examines channel and power control
Increase overall network capacity
Does not consider associations, load balancing
MDG [Broustis et al., MOBICOM 2007]
Identified tuning channel, power and associations
Studies the order in which these knobs must be tuned
Requires client modifications
32
Practical system
How do density, intelligent association, and more
channels affect capacity?
Adaptive system
Future directions
Impact of hidden terminals
Heterogeneous mix of client traffic patterns
Other backhauls: e.g. Wireless, powerline
33