Transcript Energy-based Rate Adaptation 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
2
802.11n chipset shipment
 450M+
units in 2010, >1 billion in 2012 (expected)
 Annual growth > 15%
Wi-Fi Chipset Shipments, by Protocol
(ABI Research, May 2010)
2500
2000
1500
802.11n
1000
500
2015
2014
2013
2012
2011
2010
2009
2007
2006
2005
2008
802.11a/g
0
2004
Shipments (Million)

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
4

RA is the popular mechanism to boost wireless
performance

Select the best 3-tuple MIMO setting over timevarying 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?
Goal for this Work
5

Energy perspective for RA design in 802.11n NIC
 Limitation
 Design
of traditional RA in energy savings
of EERA: Energy-based RA
Outline
6

Case Study on 802.11n RA
 Finding,

General scenarios
 Highest

goodput ≠ Energy efficiency
EERA design
 Single

root cause
client, multiple clients
Evaluation
 Comparison

Conclusion
with 3 other schemes
Case Study
7

2 MIMO RA algorithms

ARA: Atheros RA


MiRA [Mobicom’10]



Up to 3x3 antennas, triple-stream (TS) mode
Software: ath9k open source driver & HostAP
Power meter: Agilent 34401A


Zigzags between MIMO modes
802.11n NIC: Atheros AR9380 2.4/5GHz MIMO chipset


Excludes half of rates to reduce search space
An accuracy of 100uW or 10uW
Setting: AP mode; static; fixed-rate (30Mbps) UDP
Limitation 1: Energy Inefficiency
8
EE
ARA
MiRA
Goodput (Mbps)
35.4
52.4
52.5
2-min Energy (J)
69.0
106.2
105.6
Pet-bit-energy
Eb (nJ/bit)
Gap (%)
19.2
29.7
29.4
-
54.5%
52.9%
High goodput, but not energy efficiency
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
Major rates selected by ARA/MiRA
EE
HG
40.5SS
81SS
81DS
108DS
81TS
121.5TS
Why HG ≠ EE?
10

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
Limitation 2: Slow Convergence
11

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
In General Scenarios
12

Generally, HG ≠ EE
 Locations
#
of activated AP antennas
 Traffic source rate
 Power saving schemes
 SMPS:
one receiver antenna; PSMP: sleep mode
HG: 3x3/81DS
3x1
40.5SS
3x2
81DS
Data source rates
HG: 3x3/81DS
3x1
40.5SS
3x1
54SS
Power-saving schemes
Quantify NIC Energy Efficiency
13

Per-bit energy consumption: Eb
Eb =
Energy
# bits
Active
=
Non-active
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 802.11n
14

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 Design
15

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 Problem
16

On 4 dimensions
# of transmit antennas (Nt)
 # of receiver antennas (Nr)
 # of data streams (Nss)
 MCS options (NMCS)

L1: Nt
L2: Nr
1
L3: Nss
SS
L4:
SS
3
Heuristic: AP uses the
maximum number of
antennas
2
3
DS
SS
DS
TS
…
…
…
…
…
…
MCS 13.5M…135M 13.5M…135M27M… 270M 13.5M…135M 27M…270M 40.5M…405M
Ternary Search over Each Branch
17

Unimodal function:
Eb w.r.t. MCS rate
 Binary
search not
applicable

Example: 3x2/DS branch
Eb (nJ/bit)
MCS 3x2/DS
0
27
1
54
25.2
2
81
24.1
3
108
23.2
4
162
23.8
5
216
6
243
7
270
4 Steps
Simultaneous Pruning of Branches
18

Pruning over multiple branches during search:
- High-Loss pruning: loss increases - Low-loss pruning: The lower
(A)decreasing Nr, given the same MCS
bound of a setting’s per-bit
and Nss
energy from loss-free
(B)Nss, given the same MCS and Nr
goodput
3x3/81SS (26.4 nJ/bit)
3x3/108SS (∞ nJ/bit)
Eb 3x3/SS
26.6
26.5
26.4
∞
Prune 15 settings
Eb 3x3/DS Eb 3x3/TS
Eb
3x2/SS Eb
13.5
27
40.5
13.5
EERA
takes
17
probes
to
locate
the
27
54
81
27
3x1/40.5SS
121.5
51.3
40.5 29.0most81EE,
40.5 34.8
54
108 ∞ are pruned)
162 22.7
54
∞
(31 settings
∞
81
162
243
81
108
216
324
108
Sequential
search
needs
35
probes
121.5
243
364.5
121.5
135
135
270
405
Prune 8 settings
3x2/DS Eb 3x1/SS
27
54
81
108
162
216
243
270
19.2
∞
13.5
27
40.5
54
81
108
121.5
135
Is this Enough?
C1-Gput (Mbps)
19
Slow down by EERA
clients might hurt others
C2
Source rate at C1 (Mbps)
C1
…
ARA
✔
…
ARA
✗✗
ARA
EERA
EERA+: Multi-Client Operation
20

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
C1
time for each client
S1/G1
(ARA)
– Traditional MIMO RA
An epoch of time (Tep)
S2/G2
C2
(EERA+)
S3/G3
C3
(EERA+)
EERA+: Multi-Client Operation
21

Phase II: fairly allocate extra air time to EERA+
clients
 Fair
share of airtime (Fi)
Tair
S1/G1
C1
(ARA)
S2/G2
C2
(EERA+)
S3/G3
C3
(EERA+)
Fi
An epoch of time (Tep)
EERA+: Multi-Client Operation
22

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
S1/G1
C1
(ARA)
S2/G2
C2
(EERA+)
S3/G3
C3
(EERA+)
Fi
An epoch of time (Tep)
Evaluation
23

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

Single Client
24
Static UDP: at different locations, with varying AP
antennas# and PS modes
 Application: Web, VoIP, FTP, and Video streaming
 Static
interference,
mobility,
trialsscenarios
EERA
canTCP,
locate
the EE settings
in field
various

ARA well to MiRA
MRES rate
TCP/App gain: adapt
dynamic source
Static UDP
(13.4 – 35.6) % (14.3 – 36.1) % (5.8 – 26.8) %
Mobility
gain: locate
the EE settings quickly with
Static TCP
(5.1 – 20.5) % (10.4 – 32.3) % (7.3 – 23.8) %
low
probing cost
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 %
Multi-Client
25

EERA+ does not hurt coexisting non-EERA clients

C1: ARA (10Mbps50Mbps); C2: ARAEERA+
C2: EERA+
3x2
3x3
162DS 243TS
C2-Eb (nJ/bit)
C2: ARA
3x1
108SS
10 20 30 40 50
Source rate at C1 (Mbps)

10 20 30 40 50
Source rate at C1 (Mbps)
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%)

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
27

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
Backup
28
Power Save Mechanisms in 802.11n
29

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

Experimental Floorplan
30
802.11n Receiver Power Model
31

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
Pra = (a1 · Nr + f(Nss)) · BW + a2 · Nr + a3 · R + Pf

Idle power model
Pri = i1 · Nr · BW + i2 · Nr + Pf
Number of receive chains, number of streams,
and MCS rates affect both goodput and power
Power Model of an 802.11n Receiver
32

Active power model
Pra = (a1 · Nr + f(Nss)) · BW + a2 · Nr + a3 · R + Pf

Idle power model
Pri = i1 · Nr · BW + i2 · Nr + Pf
Nr: Number of receive chains
Nss: Number of streams
BW: Channel bandwidth (MHz)
R: MCS Rate (Mbps)
f(Nss)
Pf
SS
DS
TS
(mW)
i1
i2
Platform
a1
a2
a3
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
MOBICOM 2012
Power Measurement and Estimation
33
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)
MOBICOM 2012
Eb Estimation
34
Eb =
Pa × Ta + Pna × Tna
S × (Ta + Tna)
=
Pa − Pna
G
+
Pna
S
Pa, Pna: obtained from power models
G: estimated from probing
S: estimated from buffer change
Eb = (1-a) Eb (t) + a Eb
Other Issues in EERA
35

Coexistence of EERA and other MIMO RA clients


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 has an option to revert to goodput-optimizing RA mode
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?
Device-level Energy Efficiency
36

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
37

The EE setting has negligible impact on the devicelevel 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
