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
2
Author
Name:
Xinyu Zhang
Gender:
Male
Birthyear:
1984
Place of Birth:
Baotou, Inner-Mongolia, China
Nationality:
Chinese
• HIT(01)-> Toronto(05)->U Michigan(08)>(11)Princeton NEC Lab
3
Agenda
• Background
• Related Work
• Solution
▫ SRID
▫ oDoc
• Evaluation
• Conclusoin
• Comments
4
Background
• 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?
5
Existing Work
• 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
6
The E-MiLi Approach
• E-MiLi: Energy-Minimizing idle Listening
• Key Idea:
2
▫ 𝑃 ∝ 𝑉𝑑𝑑
𝑓
▫ Reduce the IL energy cost by downclocking.
• Challenge:
▫ Nyquist’s Theorem: 𝑓𝑠 > 2𝐵
▫ How to put the radio in a subconscious mode
while it can still respond to incoming packets
properly?
7
Overview of E-MiLi
What’s M-preamble
How to detect it?
When it is safe
to downclock?
8
Solutions
• 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
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SRID (1/3)
• M-preamble
Able to be detected arriving packet
even when down sampled
Duplicated Sequence
(Gold Sequence)
Embedded
Address
Check the
self-correlation
Switching
Time
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SRID (2/3)
Self-correlation of
𝑇1 samples
𝑅 𝑘
Energy level of
𝑇1 samples
𝐸 𝑘 , 𝑖𝑓 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑒𝑑
≈
0, 𝑖𝑓 𝑛𝑜𝑡 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑒𝑑
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SRID (3/3)
𝑅 𝑘
• 𝐻 < 𝑅 𝑘 𝐸 𝑘 −1 < 𝐻 −1
• Considering 𝐶 − 1 CGS
• SNR squelch
𝐸 𝑘 , 𝑖𝑓 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑒𝑑
≈
0, 𝑖𝑓 𝑛𝑜𝑡 𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑒𝑑
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Address Allocation
• 𝑛 as the embedded address
▫ Multiple user?
▫ What if 𝑛 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
▫ 𝑛 = 0, clients 𝑖 maintain a self-correlator with offset 𝑛𝐷𝑚 =
0 and 𝑛𝐷𝑚 = 𝑛𝑖 𝐷𝑚
▫ For carrier sensing purpose, double preamble is needed.
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Odoc (Opportunistic Downclocking)
• Switching time 𝑇𝑐 (9.5𝜇𝑠~151𝜇𝑠)
▫ Compared to SIFS(9~20𝜇𝑠)
• 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 𝑇𝑐
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Evaluation (1/5)
• Two Questions:
▫ Packet detecting accuracy
▫ IL energy saving
• Setups
▫ E-MiLi implementation on GNURadio
▫ Network level simulator on real WiFi trace
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Evaluation (2/5) -Packet-Detection Performance
Single link
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Evaluation (3/5) -Packet-Detection Performance
9 USRP Testbed
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Evaluation (4/5) – Energy Efficiency
Real WiFi traffic
Trace: SIGCOMM’08, PDX-powell
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Evaluation (5/5) – Energy Efficiency
Synthetic traffic
NS-2: HTTP FTP traffic generator
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Related Work
• 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)
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Conclusion
• Goal: reducing the IL energy by downclocking
▫ Sampling-Rate Invariant packet Detector
▫ Opportunistic downclocking scheme
• Future works
▫ ZigBee extension
▫ Changing working voltage
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Comments
• 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
22/20
Thank you for your attention!
Questions?
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Existing Approach
• PSM
▫ What’s PSM: Reducing idle listening time
▫ How doesn’t work: