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E- MiLi : Energy-Minimizing Idle Listening in Wireless Networks. Xinyu Zhang and Kang G. Shin Dept. of EECS Univ. Michigan. Presented by: Fenggang Wu 2011/11/04. HIT(01)-> Toronto(05)->U Michigan(08)->(11)Princeton NEC Lab. Author. Background Related Work Solution SRID o Doc
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E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks Xinyu Zhang and Kang G. Shin Dept. of EECS Univ. Michigan Presented by: Fenggang Wu 2011/11/04
HIT(01)-> Toronto(05)->U Michigan(08)->(11)Princeton NEC Lab Author
Background • Related Work • Solution • SRID • oDoc • Evaluation • Conclusoin • Comments Agenda
Scenario: • WiFi AP-client senario • Idle listening (IL) in CSMA • Why listening? (transmit, receive) • Energy waste • Problem • How to reduce the energy consumption in IL? Background
PSM • Reducing IL energy cost by reducing IL time • Yet IL still dominate clients’ energy consumption even with PSM enabled • 80% busy network, 60% idle network • Another dimension • Reducing IL energy cost by reducing IL power Existing Work
E-MiLi: Energy-Minimizing idle Listening • Key Idea: • Reduce the IL energy cost by downclocking. • Challenge: • Nyquist’s Theorem: • How to put the radio in a subconscious mode while it can still respond to incoming packets properly? The E-MiLi Approach
Overview of E-MiLi What’s M-preamble How to detect it? When it is safe to downclock?
SRID (Sampling Rate Invariant Detection) • How to perceive arriving packet in low sampling rate? • Key: separate detecting and decoding • Odoc (Opportunistic Downclocking) • When safe to downclock? • Key: predict the possibility of coming packet Solutions
M-preamble Able to be detected arriving packet even when down sampled SRID (1/3) Duplicated Sequence (Gold Sequence) Embedded Address Switching Time Check the self-correlation
SRID (2/3) Self-correlation of samples Energy level of samples
Considering CGS SNR squelch SRID (3/3)
as the embedded address • Multiple user? • What if is large? • Minimum-cost address sharing • Multiple clients share a limited number of addresses • Clients tx/rx more frequently share the addr. with less other clients • Broadcast address • , clients maintain a self-correlatorwith offset and • For carrier sensing purpose, double preamble is needed. Address Allocation
Switching time (~) • Compared to SIFS() • Arrival prediction (Outage prediction) • Key intuition: Burstininess of WiFi • Deterministic operation • CTS, DATA, ACK are all deterministic operations after RTS • Non-deterministic operation • recorded if the arriving interval if shorter than Odoc (Opportunistic Downclocking)
Two Questions: • Packet detecting accuracy • IL energy saving • Setups • E-MiLi implementation on GNURadio • Network level simulator on real WiFi trace Evaluation (1/5)
Evaluation (2/5) -Packet-Detection Performance Single link
Evaluation (3/5) -Packet-Detection Performance 9 USRP Testbed
Evaluation (4/5) – Energy Efficiency Real WiFi traffic Trace: SIGCOMM’08, PDX-powell
Evaluation (5/5) – Energy Efficiency Synthetic traffic NS-2: HTTP FTP traffic generator
Energy-efficient protocols for WiFi • PSM and its variants (can be integrated with E-MiLi) • Wakeup on demand approach (second radio needed) • Packet detection • Self-correlate (problem when down-sampled) • Cross-correlate (down-sampled prob and offset-sensitive) • Dynamic voltage-frequency scaling • In multi-processor design • SampleWidth (tx and rx agree on same clock rate) Related Work
Goal: reducing the IL energy by downclocking • Sampling-Rate Invariant packet Detector • Opportunistic downclockingscheme • Future works • ZigBee extension • Changing working voltage Conclusion
Pros: • Novel idea • Practical use • Cons: • Overhead: doesn’t consider the delay caused by the additional preamble. • Take home message: • From simple questions • Learn from real practice • Paper writer skill Comments
Questions? Thank you for your attention!
PSM • What’s PSM: Reducing idle listening time • How doesn’t work: Existing Approach