EERA: Energy-based Rate Adaption for 802.11n

ACM MOBICOM 2012Istanbul, Turkey

Chi-yu Li*, Chunyi Peng*, Songwu Lu*, Xinbing Wang+

*University of California, Los Angeles, +Shanghai Jiaotong University

Increasing Popularity of 802.11n

802.11n chipset shipment 450M+ units in 2010, >1 billion in 2012 (expected) Annual growth > 15%

2

Wi-Fi Chipset Shipments, by Protocol(ABI Research, May 2010)

802.11n

802.11a/g

2500

2000

1500

1000

500

0

Increasing Power by 802.11n 3

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)

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?

4

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

5

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

6

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

7

High goodput, but not energy efficiency

Limitation 1: Energy Inefficiency8

EE ARA MiRAGoodput (Mbps) 35.4 52.4 52.52-min Energy (J) 69.0 106.2 105.6

Pet-bit-energyEb (nJ/bit)

19.2 29.7 29.4

Gap (%) - 54.5% 52.9%

Root Cause:Highest Goodput ≠ Energy Efficiency

9

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

40.5SS 81SS 81DS 108DS 81TS 121.5TS

HG

EE

Major rates selected by ARA/MiRA

3x3/81DS

3x1/40.5SS

Why HG ≠ EE?

10

Slow down can save energy, while still accommodating traffic source

Limitation 2: Slow Convergence11

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

Generally, HG ≠ EE Locations # of activated AP antennas Traffic source rate Power saving schemes

SMPS: one receiver antenna; PSMP: sleep mode

In General Scenarios12

Data source rates

3x140.5SS

3x281DS

HG: 3x3/81DS

3x140.5SS

3x154SS

Power-saving schemes

HG: 3x3/81DS

Non-activeActive

Quantify NIC Energy Efficiency13

Eb =Energy

# bits

Pa × Ta + Pna × Tna =S × (Ta + Tna)

Rate setting Active Power model

Rate setting Idle power model Power save

scheme Rate setting goodput Traffic source rate

Tradeoff between power consumption and goodput

EERA: Energy-Based RA for 802.11n14

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?

EERA Design15

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

Multi-dimensional Search Problem16

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

L4: MCS 405M

L1: Nt

L2: Nr

L3: Nss

3

SS SS DS SS DS TS

1 2 3

13.5M 135M 135M 135M13.5M 13.5M27M 270M 270M27M 40.5M……

……

……

……

……

……

273x2/DS

54

81108

162

216

243270

MCS0

1

2

3

4

5

6

7

25.2

Eb (nJ/bit)

24.1

23.2

4 Steps

Ternary Search over Each Branch

Unimodal function: Eb w.r.t. MCS rate Binary search not

applicable

Example: 3x2/DS branch17

23.8

3x3/81SS (26.4 nJ/bit)

- Low-loss pruning: The lower bound of a setting’s per-bit energy from loss-free goodput

13.53x2/SS

13.5

81108121.5135

3x1/SS3x3/TS3x3/DS 3x2/DS

27

5440.5

81108121.5135

27

5440.5

27

162216243270

54

10881

27

162216243270

54

10881

40.5

243324364.5405

81

162121.5

Prune 8 settings3x3/108SS (∞ nJ/bit)

Simultaneous Pruning of Branches18

Pruning over multiple branches during search: - High-Loss pruning: loss increases(A)decreasing Nr, given the same MCS and Nss

(B)Nss, given the same MCS and Nr

Prune 15 settingsEb Eb Eb Eb Eb

29.0

∞

51.3∞ 22.7

34.8∞

19.2

∞

3x3/SS13.5

81108121.5135

27

5440.5

Eb

26.4∞ Sequential search needs 35 probes

EERA takes 17 probes to locate the most EE, 3x1/40.5SS

(31 settings are pruned) 26.626.5

Is this Enough?19

ARA ARA

C2C1

… ✔

ARA EERA…

✗✗

Source rate at C1 (Mbps)

Slow down by EERA clients might hurt others

EERA+: Multi-Client Operation20

Idea: An EERA+ client slows down only if other clients do

not get hurt Isolation via fair share of airtime for each client

An epoch of time (Tep)

C2(EERA+)

C1(ARA)S1/G1

S2/G2

Phase I: get the temporal air time for each client – Traditional MIMO RA

C3(EERA+)S3/G3

Tair

EERA+: Multi-Client Operation21

Phase II: fairly allocate extra air time to EERA+ clients Fair share of airtime (Fi)

An epoch of time (Tep)

C2(EERA+)

C1(ARA)S1/G1

S2/G2

C3(EERA+)S3/G3

Tair

Fi

EERA+: Multi-Client Operation22

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)

An epoch of time (Tep)

C2(EERA+)

C1(ARA)S1/G1

S2/G2

C3(EERA+)S3/G3

Tair

Fi

Evaluation23

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

ARA MiRA MRESStatic UDP (13.4 – 35.6) % (14.3 – 36.1) % (5.8 – 26.8) %

Static TCP (5.1 – 20.5) % (10.4 – 32.3) % (7.3 – 23.8) %

Application (26.5 – 33.9) % (26.6 – 35.2) % (6.7 – 36.5) %

Mobility 27.8 % 30.1 % 20.3 %

Field Trials 31.7 % 33.1 % 24.1 %

Single Client24

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

Mobility gain: locate the EE settings quickly with low probing cost

EERA can locate the EE settings in various scenariosTCP/App gain: adapt well to dynamic source rate

EERA+ does not hurt coexisting non-EERA clients C1: ARA (10Mbps50Mbps); C2: ARAEERA+

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%)

Multi-Client25

10 20 30 40 50Source rate at C1 (Mbps)

3x1108SS

3x2162DS

3x3243TS

10 20 30 40 50Source rate at C1 (Mbps)

C2: ARA C2: EERA+

Negative Impact on Device-Level Energy?26

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

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

27

28

Backup

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

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Experimental Floorplan30

Number of receive chains, number of streams, and MCS rates affect both goodput and power

802.11n Receiver Power Model31

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

Power Model of an 802.11n Receiver

MOBICOM 2012

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Active power model

Idle power model

Pra = (a1 · Nr + f(Nss)) · BW + a2 · Nr + a3 · R + Pf

Pri = i1 · Nr · BW + i2 · Nr + Pf

Platform a1 a2 a3

f(Nss) Pf (mW)

i1 i2SS DS TS

Atheros 9380 2.3 19.8 0.3 0.6 4.6 7.0 429.0 2.3 19.8

Intel 5300 3.0 195.0 0.3 3.3 4.1 4.3 496.8 2.9 195.0

Nr: Number of receive chainsNss: Number of streamsBW: Channel bandwidth (MHz)R: MCS Rate (Mbps)

Power Measurement and Estimation

MOBICOM 2012

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Power v.s. Nss (Nr/R/BW)

Power v.s. Nr (RNss/BW)

Power v.s. BW (Nr/RNss)

Power v.s. R (Nr/Nss/BW)

Eb Estimation34

Eb =Pa × Ta + Pna × Tna

S × (Ta + Tna)

Pa, Pna: obtained from power models

G: estimated from probing

=Pa − Pna

GPna

S +

S: estimated from buffer change

Eb = (1-a) Eb (t) + a Eb

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?

35

Device-level Energy Efficiency36

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

CPU State C0 C1 C2 C3

EE (3x1/40.5SS) 5.8% 0% 26.0% 66.4%

HG (3x3/81DS) 5.5% 0% 42% 52.0%

Power@800MHz (W)

16.8 |

21.3

16.8|

21.3

10.3|

13.0

9.8|

12.4

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

37