Exploiting Idle Communication Power to Improve Wireless Network

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

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 Wireless Communication • Energy consumption % > 50% total energy up to 10% total energy • A standard way to save energy – Put the WNI into sleep when idle (for a 5 V device) high power mode 450 m. A low power mode 15 m. A

802. 11 Power Saving Plan in its Basic Infrastructure Mode • 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 Internet Access Point receive data sleeping station

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 station (USENIX 04) – Limits: poorly conditioned stations suffer: fast is faster, and slow is slower. (energy: 1 bit = CPU 10, 000 cycles) ü Our work: to win both performance and energy subject to fair scheduling.

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

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

Restructure a Wireless Network to P 2 P model to Enable Multi-hop Relays To help low channel rate stations to Increase throughput and extend network coverage AP X

Effectiveness of Relays is from 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. • Fast 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 P 2 P 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 do we handle fairness? – A proxy should be given incentive for its service – For either proxy or client, the throughput and energy efficiency should be improved after relays.

Rationale • Energy efficiency: – effective number of bits delivered per energy unit • Self-incentive multi-hop relay – Use channel time to pay the relay service Proxy Client Throughput Increase üA win-win solution Energy efficiency Increase

System Model • Time based fairness in the shared radio channel ti = Dt = 1/n S 1 idle S 2 … Si 1 round … idle Sn • Consequence of multi-hop relays S 0 Sp Sq AP Proxy Client – Proxy: throughput Þidle time ¯ Þ energy efficiency – Client: channel rate Þthroughput

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. • A token bucket is used in channel scheduling. • Multi-hop relays are operated under token exchanges. • The token mechanism provides incentive to fast stations: receive more time units than relays needed.

A Token Bucket Associated with Each Station tokens from AP Token Bucket packets Packet Queue Overflow! Re-allocate to other stations by AP Transmitter 1 token per packet

Maintaining a Routing Table in AP S 1 AP Hop Station 1 Self 2 S 3 S 4 Hop Station 1 S 2 2 Self STA Proxy S 1 --S 2 --S 3 S 2 S 4 S 2 Route R(0, 2) R(2, 3) R(2, 4) Route R(0, 2) R(2, 3) S 2 S 4 S 3 Route R(0, 1) R(0, 2) R(0, 3) R(0, 4)

Put Them Together: Selfish Forwarding - SFW • Proxy discovery and selection – A poorly conditioned client broadcasts a relay request – One or more stations bet to relay with a price (tokens). AP assigns a relaying station for clients based on the second price auction in game theory. • Channel scheduling – AP distributes tokens without any enforcement. – The relaying actions are determined by token exchanges among stations. • Multi-hop routing is done by a routing table in AP

SFW System Implementation • Access Point – Net. Gear MA 311 802. 11 b PCI wireless adaptor – Host. AP linux driver version 0. 1. 3 • Wireless Stations – Net. Gear MA 401 802. 11 b PCMCIA wireless adaptor – ORi. NOCO linux driver version 0. 15 rc 2

Protocols Compared in Experiments • DCF – Most widely used protocol in 802. 11 b network – Distributed Coordination Function • TBF – Time-based Fairness (USENIX 2004) • SFW – Selfish Forwarding (our own)

Single Client Experiment 11 Mbps AP 11 Mbps slow link!

Performance Evaluation throughput (Mbps) 1 proxy (P), 1 client (Q) 16% 170% energy efficiency (Mb/J) Channel allocation scheme 266% Channel allocation scheme

Multi-clients Experiment 11 Mbps AP

Performance Evaluation 1 proxy, multiple clients Proxy throughput gain

Conclusion • Exclusive communications between AP and stations create idle communication power. • Wireless performance anomaly is an opportunity. • P 2 P based Selfish Forwarding Protocol – Improve performance and energy efficiency for everyone – Make the channel sharing and scheduling more fair. • It is easy to implement for practical usage.

Thank you!