peter a. steenkiste & dina papagiannaki 1 18-759: wireless networks l ecture 15: wifi...

Peter A. Steenkiste & Dina Papagiannaki 1

18-759: Wireless NetworksLecture 15: WiFi Self-

Organization

Dina Papagiannaki & Peter Steenkiste

Departments of Computer Science and

Electrical and Computer EngineeringSpring Semester 2009

http://www.cs.cmu.edu/~prs/wireless09/


Overview

Self-organization/Management of WiFi networks

Urban, cooperative environments (unmanaged)

» Frequency selection

» User association

» Power control

Enteprise WLANs (managed) New application domains

(unmanaged+managed)


Design of the Wired Internet

Overprovisioning the solution of choice!

Overprovisioning the solution of choice!


From a managed core to an unmanaged edge

•A large fraction of the Internet’s clients are going wireless (WiFi, 3G, WiMax)

•Client performance primarily determined by the edge network

•802.11 networks challenge our traditional thinking in network design and management

•The need for measurement paramount due to the unreliability and dynamics of the medium, the notion of contention domains and mobility


What determines client performance?

Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA)

• Transmitter senses the medium, uses Clear Channel Assessment (CCA) threshold to determine state

• If medium idle, randomize access

• When backoff counter=0, transmit

• Upon ACK, reset backoff counter

• If no ACK, double contention window, adjust transmission rate and try again

Performance = f(access probability, retransmissions, link quality, hidden terminals)


Client throughput

54 Mbps

Effective throughput~ 30 Mbps

11 Mbps

Effective throughput< 10 Mbps

1 Mbps

Effective throughput ~Kbps


Solutions and operations

Minimize the number of transmitters in the same contention domain

Ensure high quality links between clients and APs

Minimize the effect of hidden terminals

Frequency selectionPower Control

User Association

RTS/CTSScheduling


WiFi frequency selection

2.4 GHz band (802.11b/g) – 11 channels, 3 orthogonal

5 GHz band (802.11a) – 11/12 channels depending on continent

Question: Which frequency should each AP operate on for optimal performance?


Cellular analogue


3 802.11b/g frequencies not enough


WiFi scanning tools: NetStumbler


Frequency Selection

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)

(1, 6, 11)(1, 6, 11)


clientAP

Mbps/11g Client1 Client2 Client3

Before 11.81 6.86 14.37

After 30.51 (*3) 30 (*5) 29.45 (*2)

Effect of Frequency Selection


Alternatives

Interference is the outcome of transmissions! Frequency selection could take workload into

account» Requires additional measurements

» Could lead to instability if based on variable measurements


Partially overlapping channels


Using partially overlapping channels

Partially overlapped channels not considered harmful, In ACM Sigmetrics 2006


Power Control in 802.11

Heterogeneous transmit powers across nodes can lead to node starvation!

1st order starvation

We need to ensure that there is symmetry in the nodes’ contention domains.


What is the benefit of power control?

Reducing transmission power can reduce interference in the network Increasing transmission power can improve client SINR thus allowing for higher transmission rates There is a tradeoff between the amount of interference we introduce in the network and the additional throughput benefit at the client


Condition for starvation free power control

We need to ensure network symmetry We have proven that for starvation-free power control we need to keep the product of CCA threshold and transmission power constant CCA * P = C

The louder you are going to shout the more carefully you should listen for the nodes that whisper

Interference Mitigation through Power Control in High Density 802.11 WLANs, IEEE Infocom 2007


clientAP

Mbps/11g Client1 Client2 Client3

Before 11.81 6.86 14.37

After 29.45 (*3) 22.59 (*4) 30.51 (*2)

Effect of Power Control


Ensure high quality links between clients and APs

User Association


User throughput

Internet

1. Channel access time2. Aggregated transmission delay3. Wireless channel quality

State of the art can lead to unnecessarily low throughput!


User association

Balance the user associations for minimal potential delay fairness. Users take into account the personal and social cost of different association rules.

Mbps/11g Client1

Before ~ 5

After ~ 8


Overall network fairness improved

Mean:1428, variance:4378031

Mean:1559, variance: 627638


Implementation and Experimental set-up

The 3 algorithms are implemented» for both APs and clients

» on Intel 2915 prototype driver and firmware

Testbed A : U Cambridge, UK» 21 APs, 30 client

Technical Characteristics» Nodes: Soekris net4826,

» Wireless cards: Intel 2915 a/b/g

– 5-dBi omnidirectional antennae


Impact of different algorithms


Minimize the effect of hidden terminals

RTS/CTSScheduling


The transformation of enterprise WLANs

Centralization of the control – increased security, opportunity for optimal configuration


Hidden and Exposed Terminals

WLANs HP Labs Seoul National University

Our Testbed

Exposed Terminals

39% 9% 39%

Hidden Terminals

43% 70% 35%

In 30% of the hidden terminals (300 cases) performance degradation was greater than 90%!


Conflict Graph and its measurement

•Micro-probing can measure the conflict graph of a 20 node network in 20 seconds!

•No client modifications

•As accurate as state of the art with ~400 times less overheadCarrier-sense

Interference


Centralized Scheduling

(Y,C2)

(Y,C3)

(X,C4)

(X,C1)

Scheduler1 2 3 4

C1

C4

C3

C2

XY


Implementation Issues

• Need for a conflict graph• Tight synchronization among APs• Precise knowledge of when a transmission

will be over (not easy due to retransmission and changes in transmission rate)

• Speculation is required!

DCF performs better in the general case!


Hybrid Scheduling

• Use speculative centralized scheduling only for hidden terminals


The network design space

Network density

man

agem

ent

Frequency selection, power control

Centralized control and scheduling

Mor

e de

vice

s on

the

sam

e fr

eque

ncy

overhearing

PHY coding

conscious choice reachability, minimal handoff time

power control, user association

No single design will fit-all – understanding constraints and solution space is essential. Applications will be the main drivers


The FON model – large scale WiFi collaboration

home EnterpriseNeighborhood Network

Management degree


Next-generation community networks

• Community networks today seen as infrastructure for Internet access

• … and services on the move [Cabernet, ViFi, Dome]

• What if such networks formed the new Internet edge with the ability to provide better and new types of services?


Community WiFi


New Types of Services in Neighborhood WiFi

• Reliability through broadband provider diversity• Higher uplink capacity through wireless-assisted

broadband link aggregation• Services beyond the limitations of one home’s

resources

Most broadband connections underutilizedWireless speeds far exceed last mile


Today’s home use

InternetInternet

“broadband”


Large uploads are very slow!

InternetInternet

!?!

zzz..

zzz..


Burstable broadband service

InternetInternet



InternetInternet


Aggregation through wireless

What is the best strategy to get efficient aggregation of bandwidth?

Problem: Individual losses can significantly harm performance.

Wireless unicast


Opportunistic wireless reception

Wireless unicast

Opportunistic broadcast

??

?

Solution needs to minimize redundancy in wired transmissions while making optimal use of the wireless medium


Link-alike offers significant gains through

opportunism


Open Questions

• How could such a mechanism be adjusted for real-time content, such as high resolution video conferencing?

• Automated frequency selection restricts the number of APs in the same frequency, limiting the potential for overhearing

• What are the mechanisms needed for optimal performance of neighborhood networks?


US Spectrum Allocation

WiFi

700 MHz and white spaces


References

Partially-overlapped Channels not considered harmful, Arunesh Mishra, Vivek Shrivastava, Suman Banerjee, William Arbaugh. In ACM Sigmetrics, St. Malo, France, June 2006.

MDG: Measurement-Driven Guidelines for 802.11 WLAN Design, I. Broustis, K. Papagiannaki, S. Krishnamurthy, M. Faloutsos, and V. Mhatre. In ACM Mobicom, Montreal, Canada, September 2007.

Interference Mitigation through Power Control in High Density 802.11 WLANs, V. Mhatre, K. Papagiannaki and F. Baccelli. In IEEE Infocom, Anchorage, Alaska, May, 2007.

Measurement-Based Self Organization of Interfering 802.11 Wireless Access Networks, B. Kaufmann, F. Baccelli, A. Chaintreau, V. Mhatre, K. Papagiannaki and C. Diot. In IEEE Infocom, Anchorage, Alaska, May, 2007.

Link-alike: Using Wireless to Share Network Resources in a Neighborhood, S. Jakubczak, D. Andersen, M. Kaminsky, K. Papagiannaki, and S. Seshan. To appear in ACM Sigmobile Mobile Computing and Communications Review (MC2R)

peter a. steenkiste & dina papagiannaki 1 18-759: wireless networks l ecture 15: wifi...

Documents

steenkiste dina papagiannaki

netstumbler slide

mobility slide

wifi frequency selection

cellular analogue slide

mbps effective throughput

client throughput

wireless wifi