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EERA: Energy-based Rate Adaption for 802.11n

EERA: Energy-based Rate Adaption for 802.11n. Chi-yu Li * , Chunyi Peng * , Songwu Lu * , Xinbing Wang + * University of California, Los Angeles, + Shanghai Jiaotong University. ACM MOBICOM 2012 Istanbul, Turkey. Increasing Popularity of 802.11n. 802.11n chipset shipment

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EERA: Energy-based Rate Adaption for 802.11n

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  1. EERA: Energy-based Rate Adaption for 802.11n Chi-yu Li*, Chunyi Peng*, Songwu Lu*, Xinbing Wang+ *University of California, Los Angeles, +Shanghai Jiaotong University ACM MOBICOM 2012 Istanbul, Turkey

  2. Increasing Popularity of 802.11n • 802.11n chipset shipment • 450M+ units in 2010, >1 billion in 2012 (expected) • Annual growth > 15% 2500 2000 1500 1000 500 0 Wi-Fi Chipset Shipments, by Protocol (ABI Research, May 2010) Shipments (Million) 802.11n 802.11a/g 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

  3. Increasing Power by 802.11n • Higher power consumption compared with legacy 802.11a • 3x3 MIMO RX: 2x during active • 3x3 MIMO RX: 1.5x during idle • Even higher if more antennas are used (up to 8 for 802.11ac)

  4. 802.11n Rate Adaptation • RA is the popular mechanism to boost wireless performance • Select the best 3-tuple MIMO setting over time-varying channel • Modulation and coding scheme (MCS): 6.5Mbps, …, 600Mbps • Number of activated antennas: 1, …, 4 • Stream modes: SS, DS, TS, QS • Traditional design goal: Highest goodput What about energy efficiency?

  5. Goal for this Work • Energy perspective for RA design in 802.11n NIC • Limitation of traditional RA in energy savings • Design of EERA: Energy-based RA

  6. Outline • Case Study on 802.11n RA • Finding, root cause • General scenarios • Highest goodput ≠ Energy efficiency • EERA design • Single client, multiple clients • Evaluation • Comparison with 3 other schemes • Conclusion

  7. Case Study • 2 MIMO RA algorithms • ARA: Atheros RA • Excludes half of rates to reduce search space • MiRA [Mobicom’10] • Zigzags between MIMO modes • 802.11n NIC: Atheros AR9380 2.4/5GHz MIMO chipset • Up to 3x3 antennas, triple-stream (TS) mode • Software: ath9k open source driver & HostAP • Power meter: Agilent 34401A • An accuracy of 100uW or 10uW • Setting: AP mode; static; fixed-rate (30Mbps) UDP

  8. Limitation 1: Energy Inefficiency High goodput, but not energy efficiency

  9. Root Cause:Highest Goodput ≠ Energy Efficiency • EE v.s. Highest-Goodput (HG) settings • The gap between EE and HG reaches 11.1 nJ/bit • Incurring energy waste 57.8% using HG Major rates selected by ARA/MiRA EE HG 40.5SS 81SS 81DS 108DS 81TS 121.5TS

  10. Why HG ≠ EE? • More antennas and more streams activated for higher goodput • Small goodput gain at a high energy cost 3x1/40.5SS 3x3/81DS Slow down can save energy, while still accommodating traffic source

  11. Limitation 2: Slow Convergence • Multiple rounds to reach HG setting by ARA and MiRA • Root cause: Sequential search Scaling issue in many-antenna 802.11x: 360 options in 8-antenna 802.11ac vs. 48 options in 3-antenna 802.11n

  12. In General Scenarios • Generally, HG ≠ EE • Locations • # of activated AP antennas • Traffic source rate • Power saving schemes • SMPS: one receiver antenna; PSMP: sleep mode HG: 3x3/81DS HG: 3x3/81DS 3x1 40.5SS 3x1 40.5SS 3x1 54SS 3x2 81DS Power-saving schemes Data source rates

  13. Quantify NIC Energy Efficiency • Per-bit energy consumption: Eb • Rate setting • Active Power model Energy Eb = # bits • Rate setting • Idle power model • Power save scheme Pa × Ta + Pna × Tna = Non-active Active S× (Ta + Tna) • Rate setting  goodput • Traffic source rate Tradeoff between power consumption and goodput

  14. EERA: Energy-Based RA for 802.11n • Idea: Slow down to save energy • tradeoff goodput for energy efficiency • but still accommodate the data source • How to locate slow rate for energy saving? • How to locate it faster? • How to control the degree of slowdown?

  15. EERA Design • Single-client: • How to locate the low-energy MIMO setting • Search over multi-level tree • Ternary search over each branch • Simultaneous pruning by leveraging MIMO features • Multi-client: on top of single-client design • How to prevent each client from affecting others due to its slowdown • Ensure fair share of airtime by each client • Tradeoff between energy efficiency and fairness

  16. Multi-dimensional Search Problem • On 4 dimensions • # of transmit antennas (Nt) • # of receiver antennas (Nr) • # of data streams (Nss) • MCS options (NMCS) Heuristic: AP uses the maximum number of antennas L1: Nt 3 L2: Nr 1 2 3 SS SS L3: Nss SS DS DS TS …… …… …… …… …… …… L4: MCS 405M 27M 13.5M 135M 13.5M 135M 270M 13.5M 135M 27M 270M 40.5M

  17. Ternary Search over Each Branch • Unimodal function: Eb w.r.t. MCS rate • Binary search not applicable • Example: 3x2/DS branch MCS 3x2/DS Eb (nJ/bit) 0 27 1 54 25.2 2 81 108 24.1 3 23.2 4 162 23.8 216 5 6 243 4 Steps 270 7

  18. Simultaneous Pruning of Branches • Pruning over multiple branches during search: • - High-Loss pruning: loss increases • decreasing Nr, given the same MCS and Nss • Nss, given the same MCS and Nr - Low-loss pruning: The lower bound of a setting’s per-bit energy from loss-free goodput 3x3/108SS (∞ nJ/bit) 3x3/81SS (26.4 nJ/bit) Prune 15 settings Prune 8 settings Eb 3x3/SS Eb 3x3/DS Eb Eb 3x3/TS Eb 3x2/SS Eb 3x2/DS 3x1/SS 13.5 27 13.5 27 40.5 13.5 EERA takes 17 probes to locate the most EE, 3x1/40.5SS (31 settings are pruned) 27 54 27 54 81 27 121.5 51.3 40.5 19.2 26.6 81 34.8 40.5 81 40.5 29.0 ∞ 54 ∞ 26.5 108 54 108 162 54 22.7 ∞ ∞ 81 162 26.4 81 162 243 81 ∞ 108 216 108 216 324 108 Sequential search needs 35 probes 121.5 243 121.5 243 364.5 121.5 135 270 135 135 270 405

  19. Is this Enough? • Slow down by EERA clients might hurt others C1 C2 C1-Gput (Mbps) ✔ … ARA ARA … ARA EERA Source rate at C1 (Mbps) ✗ ✗

  20. EERA+: Multi-Client Operation • Idea: • An EERA+ client slows down only if other clients do not get hurt • Isolation via fair share of airtime for each client Tair Phase I: get the temporal air time for each client – Traditional MIMO RA C1 (ARA) S1/G1 C2 (EERA+) S2/G2 C3 (EERA+) S3/G3 An epoch of time (Tep)

  21. EERA+: Multi-Client Operation • Phase II: fairly allocate extra air time to EERA+ clients • Fair share of airtime (Fi) Tair C1 (ARA) S1/G1 Fi C2 (EERA+) S2/G2 C3 (EERA+) S3/G3 An epoch of time (Tep)

  22. EERA+: Multi-Client Operation • Phase III: Client i selects the most EE setting given the constraint Fi • Prune the settings which are too slow to accommodate Si(EERA operation) Tair C1 (ARA) S1/G1 Fi C2 (EERA+) S2/G2 C3 (EERA+) S3/G3 An epoch of time (Tep)

  23. Evaluation • Comparing EERA with ARA, MiRA, and MRES • MRES[ICNP’11]: improve EE by adjusting the number of antennas on top of RA • Scenarios • Single Client • Static, mobility, interference, power-saving modes, wireless configurations, … • Multi-Client • Multiple EERA/EERA+ clients • Coexistence with EERA/EERA+ and non-EERA clients

  24. Single Client • Static UDP: at different locations, with varying AP antennas# and PS modes • Application: Web, VoIP, FTP, and Video streaming • Static TCP, interference, mobility, field trials EERA can locate the EE settings in various scenarios TCP/App gain: adapt well to dynamic source rate Mobility gain: locate the EE settings quickly with low probing cost

  25. Multi-Client C2: ARA C2: EERA+ • EERA+ does not hurt coexisting non-EERA clients • C1: ARA (10Mbps50Mbps); C2: ARAEERA+ • Slowdown overhead: delay increase • Multiple EERA clients: < 0.2 ms per packet (< 14.2%) • Coexistence of EERA/ARA: <0.08 ms per packet (<5.3%) 3x1 108SS 3x2 162DS 3x3 243TS C2-Eb (nJ/bit) 10 20 30 40 50 10 20 30 40 50 Source rate at C1 (Mbps) Source rate at C1 (Mbps)

  26. Negative Impact on Device-Level Energy? • Slowdown may increase energy of other components: • Two dominant components • Display: its energy independent of NIC status • CPU: its status only slightly changed due to slowdown • Quantify the impact with applications • Applications: Web, VoIP, FTP, and Video streaming • There are negligible impacts on all of them except FTP • Why FTP? FTP stops once a file transfer completes

  27. Summary • Limitations of goodput-optimizing RAs • Goodput ≠ Energy Efficiency @NIC • Slow convergence due to sequential search • EERA: Energy-based RA for 802.11n NIC • Ternary search + simultaneous branch pruning • Slow down limited by fair share of airtime • Insights: • Tradeoff between speed and energy • Tradeoff between fairness and energy

  28. Backup

  29. Power Save Mechanisms in 802.11n • Spatial Multiplexing Power Save (SMPS) • Static SMPS: the client statically retains a single receive chain • Dynamic SMPS: the client switches to multiple receive chains during data transmission, but shifts back to one chain afterwards. • Power Save Multi-Poll (PSMP) • Scheduled PSMP (S-PSMP): AP periodically initiates a PSMP sequence to schedule the transmission • Unscheduled PSMP (U-PSMP): AP starts an unscheduled sequence and delivers to those wakeup clients

  30. Experimental Floorplan

  31. 802.11n Receiver Power Model • Goodput is affected by • Number of receive chains (Nr), number of streams (Nss), and MCS rates (R) • The power of an 802.11n receiver • Active power model • Idle power model Pra = (a1 · Nr + f(Nss)) · BW + a2 · Nr + a3 · R + Pf Pri = i1 · Nr · BW + i2 · Nr + Pf Number of receive chains, number of streams, and MCS rates affect both goodput and power

  32. Power Model of an 802.11n Receiver • Active power model • Idle power model Pra = (a1 · Nr + f(Nss)) · BW + a2 · Nr + a3 · R + Pf Nr: Number of receive chains Nss: Number of streams BW: Channel bandwidth (MHz) R: MCS Rate (Mbps) Pri = i1 · Nr · BW + i2 · Nr + Pf

  33. Power Measurement and Estimation Power v.s. Nss (Nr/R/BW) Power v.s. BW (Nr/RNss) Power v.s. Nr (RNss/BW) Power v.s. R (Nr/Nss/BW)

  34. Eb Estimation Pa − Pna Pa × Ta + Pna × Tna = + Eb = G S× (Ta + Tna) Pa,Pna: obtained from power models Pna S G: estimated from probing S: estimated from buffer change Eb = (1-a) Eb (t) + a Eb

  35. Other Issues in EERA • Coexistence of EERA and other MIMO RA clients • EERA has an option to revert to goodput-optimizing RA mode • Greedy clients • EERA sets the pre-configured parameter Ri : how much goodput the client is willing to give up for energy saving • Uplink case • EERA seek to minimize (Pa(tx) – Pi) / GUL • AP calculates fair share for each uplink/downlink client, and then notify it of its uplink airtime share • Ad-hoc mode: not supported due to two challenges • How to allocate fair share of airtime in the multihop setting? • How to coordinate RA operations among multiple clients in a fully distributed manner?

  36. Device-level Energy Efficiency • Any impact on the energy consumption of other device components? • Consider Display and CPU: the dominant portion of device’s energy consumption • Device: ASUS F8S laptop with Intel Core2 Duo T8300 CPU • Display energy consumption is independent of the NIC status • CPU status can be slightly changed due to slower transmission

  37. In Real Application Scenarios • The EE setting has negligible impact on the device-level energy consumption except in the FTP case • FTP in HG stops consuming more energy once a file transfer completes • The other applications include UDP flow (30Mbps), Web, VoIP, Video streaming

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