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