Idle Communication Power

1. Exploiting Idle Communication Power to Improve Wireless Network Performance and Energy Efficiency Lei Guo, Xiaoning Ding, Haining Wang, Qun Li, Songqing Chen, and Xiaodong Zhang

2. 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?

3. 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) up to 10% total energy > 50% total energy high power mode 450 mA low power mode 15 mA

4. 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 Traffic Indication Map (TIM) wake up poll receive data 802.11 Power Saving Mechanism Internet AccessPoint sleeping station

5. 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

6. 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 winboth performance and energy

7. While the channel is used by one station, idle communication power is wasted in many other stations AP Source of Idle Communication Power Wireless performance anomaly makes this power waste worse, but also with an opportunity.

8. Outline • Motivation and rationale • System model and algorithms • System design and implementation • Performance evaluation • Conclusion

9. To help low channel rate stations to Increase throughput and extend network coverage AP X Multi-hop Relay

10. 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.

11. 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.

12. 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

13. ti=Dt = 1/n Sp S0 Sq S1 S2 … Si … Sn AP Proxy Client 1 round System Model • Time based fairness in shared radio channel • Principle of proxy forwarding • Proxy: throughput ­ Þ idle time ¯ Þ energy/bit ¯ • Client: channel rate ­ Þ throughput ­ idle idle

14. 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

15. Token and Token Bucket Model tokens from AP Overflow! Re-allocate to other stations by AP Token Bucket Transmitter 1 token per packet packets Packet Queue

16. Multi-hop forwarding S1 AP S2 S4 S3

17. 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

18. 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

19. Protocols Compared • DCF • Most widely used protocol in 802.11b network • Distributed Coordination Function • TBF • Time-based Fairness (USENIX 2004) • SFW • Selfish Forwarding

20. AP Single Client Experiment 11Mbps 11Mbps 1Mbps

21. Channel allocation scheme Channel allocation scheme Performance Evaluation 1 proxy (P), 1 client (Q)

22. AP Multi-clients Experiment 11Mbps 1Mbps

23. Performance Evaluation 1 proxy, multiple clients Proxy throughput gain

24. 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

25. Thank you!