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Snooze: Energy Management in 802.11n WLANs

Snooze: Energy Management in 802.11n WLANs. Ki-Young Jang, Shuai Hao , Anmol Sheth , Ramesh Govindan. Background. Evolution of Wi-Fi. Mbps. 8x speedup compared to 802.11a/g. Performance vs. Energy Usage. MIMO higher data rate spatial diversity. Background.

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Snooze: Energy Management in 802.11n WLANs

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  1. Snooze: Energy Management in 802.11n WLANs Ki-Young Jang, ShuaiHao, AnmolSheth, Ramesh Govindan

  2. Background Evolution of Wi-Fi Mbps 8x speedup compared to 802.11a/g Performance vs. Energy Usage

  3. MIMO • higher data rate • spatial diversity Background 802.11n Features and Energy Usage Intel Wi - Fi Link 5300(W) # of Antenna Tx Rx Idle Sleep A B 1 1.28 0.94 0.82 0.10 2 1.99 1.27 1.13 0.10 3 2.10 1.60 1.45 0.10 1.5x and 1.6x 1.3x and 1.7x Additional power states: 10-30% of peak power consumption of the tablet! Energy management should exploit both sleep opportunities and antenna configuration.

  4. Motivation Design ImplementationEvaluation Motivation Micro-sleep Opportunities A t Z Z Z Z Z Z Sleep! t AP t B Sleep!

  5. Motivation Design ImplementationEvaluation Motivation Micro-sleep Opportunities Depending on the traffic and number of clients, we can get energy savings of 30% ~ 90%. # of STA 1 Sleeping while AP is servicing others Traffic 2 Sleeping during inter-frame gaps Sleep + Wakeup = ~2ms Micro-sleep

  6. Motivation Design ImplementationEvaluation Motivation Antenna Configuration Antenna configuration should be adaptive based on traffic demand and link quality. High bandwidth scenario: MIMO3 is best Internet as bottleneck: SISO is best

  7. Micro-sleep with minimal impact on delay and throughput-sensitive traffic Adaptive antenna configuration management Joint design of both mechanisms Application agnostic Challenges Sleep for 70ms Power(W) Sleep for 50ms 100 200 300 Time (ms)

  8. Contribution Design and Implementation of Snooze Joint, application-agnostic design of client micro-sleepand antenna configuration management. Extensive experiments that demonstrate 30~85% energy-savings over CAM across a wide range of traffic scenarios.

  9. Motivation Design ImplementationEvaluation AP-Directed Design Goal: Reduce client energy consumption by jointly controlling sleep and antenna configuration Snooze AP • Shapes traffic to create sleep opportunities • Minimal impact on traffic • Minimizes the number of active clients • Manages antenna configurations • Minimizes antennas needed Snooze Client

  10. Motivation Design ImplementationEvaluation Snooze Components Micro-sleep Scheduling Antenna Mgmt. Hysteresis and moving averages • Sleep duration: based on measured packet arrival rate • Awake duration: based on average airtime consumption • If measured airtime utilization is • < 0.3: high link quality or more antennas -> turn off 1 antenna • > 0.7: low link quality or less antennas -> turn on 1 antenna • Rate Adaptation: AP uses default rate-control algorithm with restricted search space A: 1Mbps B: 20Mbps Time (Second)

  11. Motivation Design ImplementationEvaluation Implementation AP Client Airtime Scheduling Sleep/Wakeup Computation Kernel Per client traffic queue ... mac80211 mac80211 Antenna Configuration Sleep/ Wakeup Rate Table Airtime Usage Driver iwlagn iwlagn

  12. Motivation Design Implementation Evaluation Evaluation Overview and Setup

  13. Motivation Design Implementation Evaluation Evaluation High Definition Video Streaming More than 25% low-power sleeping compared with both CAM and PSM About 50% energy savings compared with both CAM and PSM Average delay CAM : 2.5ms, PSM : 4ms, Snooze : 8ms

  14. Motivation Design Implementation Evaluation Evaluation Heterogeneous Traffic micro-sleep Client antenna config. Mode File VoIP HD Chat Snooze can accommodate multiple concurrent applications. One app per client Energy saving breakdown Both techniques contribute significantly to energy savings, but contribution varies across traffic.

  15. Related Work Energy Management Techniques for 802.11

  16. Conclusion Snooze: Energy Management Scheme for 802.11n • Client micro-sleep and antenna configuration management • Application agnostic • 30~85% energy saving across a wide range of traffic scenarios Future Work • Multi-AP setting • Highly bursty workloads • Parameter sensitivity

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