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EERA: Energy-based Rate Adaption for 802.11n
ACM MOBICOM 2012
Istanbul, 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 MiRA
Goodput (Mbps) 35.4 52.4 52.5
2-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……
……
……
……
……
……
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3x2/DS
54
81
108
162
216
243
270
MCS
0
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 branch
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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
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5440.5
81108121.5135
27
5440.5
27
162216243270
54
10881
27
162216243270
54
10881
40.5
243324364.5405
81
162
121.5
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 settings
Eb Eb Eb Eb Eb
29.0
∞
51.3∞ 22.7
34.8∞
19.2
∞
3x3/SS13.5
81108121.5135
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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 MRES
Static 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 scenarios
TCP/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
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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
G
Pna
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?
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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
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