Idle Communication PowerIdle Communication Power

Lei Guo, Xiaoning Ding, Haining Wang, Qun Li,

Songqing Chen, and Xiaodong Zhang

ExploitingExploiting

to Improve Wireless Network to Improve Wireless Network Performance and Energy EfficiencyPerformance and Energy Efficiency

Challenges in Wireless System Design

• Energy saving is not easy– Limited battery capacity in wireless devices – High power consumption in wireless communication

• High performance costs energy and fairness – Wireless users demand high throughput, but …– A high throughput device needs less sleep. – A channel allocation mechanism can favor some but

degrade performance of others.

• Can we win both instead of addressing the trade-off?

Power Consumption for Mobile Devices

• Energy consumption

• A simple way to save energy

– Put the WNI into sleep mode when idle (for a 5 V device)

> 50% total energy

up to 10%total energy

high power mode450 mA

low power mode15 mA

802.11 Power Saving Mechanism• Access point

– Buffer data for sleeping stations

– Broadcast beacon with TIM periodically (100 ms)

• Sleeping station– Wake up periodically to

receive beacon– Poll access point to receive

data– Sleep again

Access Point

Internet

Traffic Indication Map (TIM)

sleeping station

wake uppoll

receive data

Observations of IEEE 802.11 Protocol • A client/server model

– Each station independently communicates with AP– AP serves a station one at a time via the channel.

• The saving mode affects TCP traffic– Increasing RTT and decreasing throughput.

• Performance anomaly (Infocom’03)– Non-uniform transfer rates between different stations to

AP due to distance and obstacle condition differences. – A low speed station has low channel utilization rate.

• Waste energy while a station is waiting for its turn.– Idle communication power due to strong dependency

Existing Solutions to address the Limits

• Reducing idle communication power by– Traffic prediction: bounded slowdown (MOBICOM’02)– Self-tuning with application hints (MOBICOM’03)– Limits: case by case, and accuracy can vary.

• Address the performance anomaly– Time-based fairness scheduling: a constant time unit is

given to each device (USENIX 04) – Limits: poorly conditioned devices suffer: fast is faster,

and slow is slower.

Our work: to win both performance and energy

Source of Idle Communication PowerWhile the channel is used by one station, idle communication power is wasted in many other stations

AP

Wireless performance anomaly makes this power waste worse, but also with an opportunity.

Outline

• Motivation and rationale

• System model and algorithms

• System design and implementation

• Performance evaluation

• Conclusion

Multi-hop RelayTo help low channel rate stations to Increase throughput and extend network coverage

AP

X

Multi-hop Relays Leverage Strong Dependency • Slow stations become faster

– Completing the data transfer ahead of the unit time.– Equivalent to move the station closer to AP or improve

the station’s communication condition.

• Faster stations serve as proxies for slow stations– Performance improvement of slow stations reduced the

waste of idle communication powers of fast stations --- shortening the waiting time.

• Effective P2P coordination among stations is the key.

Incentive and Fairness to Fast Stations

• Why not sleep or wait, but proxy/relay for others?– Sleep lowers throughput, and wait wastes energy. – Idle communication energy can be used – The saved time in slow stations should be contributed.

• How much service is fair in a shared radio channel?– A proxy should be paid for its service– For either proxy or client, the throughput and energy

utilization should be improved.

Rationale

• Energy efficiency: what does a user care about?– Energy per second

– Energy per bit: time is energy• Self-incentive multi-hop relay with TBF

– Use channel time to pay the relay service

A win-win solution

Throughput Energy efficiency

Proxy Increase No loss

Client Increase Increase

System Model• Time based fairness in shared radio channel

• Principle of proxy forwarding

– Proxy: throughput idle time energy/bit – Client: channel rate throughput

S1 S2 … Si … Sn

ti = t = 1/n

1 roundidle idle

Sq

Client

Sp

Proxy

S0

AP

Basic Idea of Token-based Channel Scheduling

• A token is a ticket for a data transfer (RX/TX) in one time unit

• AP initially distributes an equal amount of tokens to each station (fairness).

• A pair of RX & TX consumes one token.• Token bucket model to fully use transmission

channel.• Multi-hop forwarding to increase throughput• Incentive rewards to proxies

packets

Token and Token Bucket Modeltokens from AP

Overflow!Re-allocate to other

stations by AP

Token Bucket

Packet Queue

Transmitter 1 token per packet

Multi-hop forwarding

APS1

STA Proxy RateS1 --- R(0,1)S2 --- R(0,2)S3 S2 R(0,3)S4 S2 R(0,4)

S2

S3

S4

Hop Station Rate1 Self R(0,2)2 S3 R(2,3)

S4 R(2,4)

Hop Station Rate1 S2 R(0,2)2 Self R(2,3)

Put Them Together: Selfish Forwarding - SFW

• Proxy discovery and selection– A poorly conditioned client broadcasts a request to relay his

packets

– AP assigns a relaying station for clients based on the game theory (second price auction) to provide fairness for competition among proxy candidates

• Channel scheduling– AP distributes tokens for fairness without any enforcement.

– The replaying actions are determined by token exchanges among stations.

• Multi-hop routing

Implementation

• AP– NetGear MA311 802.11b PCI wireless adaptor– HostAP linux driver version 0.1.3

• Wireless Stations– NetGear MA401 802.11b PCMCIA wireless

adaptor– ORiNOCO linux driver version 0.15rc2

Protocols Compared

• DCF– Most widely used protocol in 802.11b network– Distributed Coordination Function

• TBF– Time-based Fairness (USENIX 2004)

• SFW– Selfish Forwarding

Single Client Experiment

AP

11Mbps

11Mbps

1Mbps

Channel allocation scheme

Channel allocation scheme

Performance Evaluation1 proxy (P), 1 client (Q)

Multi-clients Experiment

AP

11Mbps

1Mbps

Performance Evaluation

Proxy throughput gain

1 proxy, multiple clients

Conclusion

• Idle communication power in TCP sessions

• Energy efficiency metric: task based

• Cooperative relay service– Peer-to-peer– Win-win solution

• System design and prototype implementation

Thank you!Thank you!