Presentation of the paper "Experimental Evaluation of Reverse Direction Transmissions in WLAN Using the WARP Platform" at the IEEE International Conference on Communications (IEEE ICC 2015)
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Experimental Evaluation of Reverse Direction Transmissions in WLAN Using the WARP Platform
1. IEEE ICC 2015, 8–12 June, London, UK
Raul Palaciosa, Francesco Francha, Francisco Vazquez-Gallegob, Jesus
Alonso-Zarateb, and Fabrizio Granellia
aDISI, University of Trento, Italy
bCTTC, Barcelona, Spain
Experimental Evaluation of Reverse Direction
Transmissions in WLAN Using the WARP Platform
2. 2
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Outline
Scope
•Wi-Fi Footprint
•IEEE 802.11
MAC Layer
•Energy Issues
•Weaknesses of
Theoretical
Analyses and
Simulations
Contribution
•BidMAC:
Reactive
Reverse
Direction TXs
•Implementing
BidMAC on
WARPv3
•Experiments
Outcome
•Energy
Efficiency
•Net/AP/STAs
•Vs. Traffic
Load
•Vs. Data
packet Length
•Vs. PHY Data
Rate
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Residential
Public
Enterprise
WLAN AP
(Wi-Fi) User Wi-Fi-enabled
devices
The Big Picture
Source: Wireless Broadband Alliance (WBA), Informa, Nov. 2011
• Wide deployment
of Wi-Fi hotspots
worldwide.
• Increasing
diversity of Wi-Fi-
enabled devices.
3.300.000
Public Hotspots Worldwide in 2013
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Wi-Fi Footprint
• The number of Wi-Fi public hotspots will increase by 350% from 2011 to 2015.
• Wi-Fi home and hotspots will contribute by 31%-34% to the overall yearly cloud
energy consumption, being the second main contributor after mobile networks.
Source: The Power of Wireless Cloud, Alcatel-Lucent’s Bell Labs, Centre for
Energy-Efficient Telecommunications (CEET), University of Melbourne, Apr. 2013
Source: Wireless Broadband Access (WBA), Informa, Nov. 2011
1%
1%
2009 2010 2011 2012 2013 2014 2015
0.5
0.8
1.3
2.1
3.3
4.5
5.8
350%
Number of Wi-Fi Public Hotspots in the World
(in million), 2009-2015
Metro & Core Networks
Data centers
Local (Wi-Fi Home/Wi-Fi Hotspots)
Mobile access networks (4G LTE)
2012 2015 Lo 2015 Hi
9173
32424
42957
57%
55%
59%
16%
26%
1%
34%
31%10%
9%
Total Annual Wireless Cloud Energy Consumption (GWh),
2012-2015
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Nokia N95 Energy Consumption
• Downloading data using the WLAN radio interface consumes more
energy that what is consumed by the CPU or the display in a Nokia
N95 smart phone.
N95 8GB
Downloading data
using HSDPA
Downloading data
using WLAN
Sending an SMS
Making a voice call
Playing an MP3 file
Display backlight
Normalisedenergyconsumption(%)
100
90
80
70
60
50
40
30
20
10
0
Source: Nokia Research Centre, 2012
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Energy Efficiency via the MAC Layer
MAC
PHY
NET
Channel
Status
Transmission
Control
Reliable
data
Routing
information
Takes decisions on the
usage of the wireless
interface to regulate the
access to the channel
Best place for energy
consumption control and
energy saving through
cross-layer methods
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DCF Example (With RTS/CTS)
STA1
AP
Other
STAs
RTS
CTS
DATA
ACK
TDIFS TDIFSTSIFS TSIFS TSIFS
T0
CTS
TSIFS TSIFS TSIFS
Time +
ACK
Time +
Time +
NAV RTS
RTS DATA
NAV CTS
NAV DATA
NAV RTS
NAV CTS
NAV DATA
Pi
Pt Pr
PtPr
T1
Pi
Pr
Pi
TDIFSTBO TRTS TDATA TCTS TACKTCTS TACK TRTS TDATATBO
DIFS SIFS SIFS SIFS DIFS SIFS SIFS SIFS DIFS
RTS/CTS exchange RTS/CTS exchange
AP: Access Point
STA: Wireless Station
DIFS: DCF Interframe
Space
SIFS: Short Interframe
Space
RTS: Request-To-Send
CTS: Clear-To-Send
ACK: Acknowledgment
NAV: Network Allocation
Vector
BO: Slotted Backoff Time
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DCF Energy Inefficiencies
Control packet overhead
Silent and backoff periods
Idle listening and overhearing
Collisions of control and data packets
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IEEE 802.11n RDP
RDP
Allocate
unused
TXOP time
To one or
more
receivers
Reverse
direction
transfer
Good for
bidirectional
traffic
Reduce
channel
contention
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Proactive RD
Protocols [1],[2]
•RD transfer initiated
by the transmitter
•Grant remaining
TXOP duration
•Based on 802.11n
RDP operation
Types of RD-based Protocols
Reactive RD
Protocols [3]-[6]
•RD transfer initiated
by the receiver
•Reserve extended
TXOP duration
•More adaptive to
receiver needs
[1] M. Ozdemir, G. Daqing, A. B. McDonald, and J. Zhang, “Enhancing MAC Performance with a Reverse
Direction Protocol for High-Capacity Wireless LANs,” in IEEE VTC 2006, Sep. 2006, pp. 1–5.
[2] D.Akhmetov,“802.11n: Performance Results of Reverse Direction Data Flow,” in IEEE PIMRC 2006, Sep.
2006, pp. 1–3.
[3] H. Wu, Y. Peng, K. Long, S. Cheng, and J. Ma, “Performance of Reliable Transport Protocol over IEEE
802.11 Wireless LAN: Analysis and Enhancement,” in IEEE INFOCOM 2002, vol. 2, Jun. 2002, pp. 599–607.
[4] D.-H. Kwon, W.-J. Kim, and Y.-J. Suh, “A Bidirectional Data Transfer Protocol for Capacity and
Throughput Enhancements in Multi-rate Wireless LANs,” in IEEE VTC 2004, vol. 4, Sep. 2004, pp. 3055–3059.
[5] W. Choi, J. Han, B. J. Park, and J. Hong, “BCTMA (Bi-directional Cut- Through Medium Access) Protocol
for 802.11-based Multi-hop Wireless Networks,” in ACM ISSADS 2005, Jan. 2005, pp. 377–387.
[6] N. S. P. Nandiraju, H. Gossain, D. Cavalcanti, K. R. Chowdhury, and D. P. Agrawal, “Achieving Fairness
in Wireless LANs by Enhanced IEEE 802.11 DCF,” in IEEE WiMob 2006, Jun. 2006, pp. 132–139.
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BidMAC [7],[8]: A Reactive RD
Protocol for Infrastructure WLANs
BidMAC
Receiver-
initiated
bidirectional
transmissions
Transmit data
after
receiving
data
Backwards
compatible
with IEEE
802.11 DCF Balanced
DL/UL
channel
share
Improved
WLAN
performance
[7] R. Palacios, F. Granelli, D. Gajic, and A. Foglar, “An Energy-Efficient
MAC Protocol for Infrastructure WLAN Based on Modified PCF/DCF
Access Schemes Using a Bidirectional Data Packet Exchange,” in IEEE
CAMAD 2012, Sep. 2012, pp. 216–220.
[8] R. Palacios, F. Granelli, D. Kliazovich, L. Alonso, and J. Alonso- Zarate,
“Energy Efficiency of an Enhanced DCF Access Method Using
Bidirectional Communications for Infrastructure-based IEEE 802.11
WLANs,” in IEEE CAMAD 2013, Sep. 2013, pp. 38–42.
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BidMAC Example (Without
RTS/CTS)
AP: Access Point
STA: Wireless Station
DIFS: DCF Interframe
Space
SIFS: Short Interframe
Space
ACK: Acknowledgment
NAV: Network Allocation
Vector
BO: Slotted Backoff Time
RD: Reverse Direction
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Motivations of The Paper
Analysis
No channel
errors
No collisions
Infinite queues
Saturated
conditions
Simulation
No channel
errors
Infinite queues
Infinite
retransmissions
No underlying
physical layer
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Anlys
Simul
Exp
Complete
performance
assessment
802.11g
DCF
BidMAC
Contributions of The Paper
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MAC Prototyping Platforms
WARP
• Wi-Fi compliant
• Flexible
• Open source
Platforms
TUTWLAN
WARP
CALRADIO
USRP
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WARPv3 and Its HW Features
RF Interface B
RF Interface A
Virtex-6
FPGA
LX240T
UserI/O
DDR3-SO-DIMM
Slot
FMC HPC Slot
Ethernet
A
Ethernet
B
UserI/O
JTAG
SDCard
Power
Supply
Power
Switch
UART
I/O header
Displays
DIPswitch
Fig. 2. WARP v3 and its hardware features [13], [14].
analyzed. In contrast, EA P sat
D C F is obtained when the AP ca
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Testbed Layout
1 m
1m
1m
PC 1
PC 2 PC 3
Experiment
Controller
+
Energino
Software
E 2 E 3
E 1
Switch
PWC 2 PWC 3
PWC 1
WARP
STA 2
WARP
STA 1
Wired System:
Gigabit
Ethernet
NetworkWireless System:
IEEE 802.11g
WLAN
WARP
AP
Energino
Software
PWC: 12 V Power
Charger
E: Energino Shield
+ Arduino Board
EPS: 9 V External
Power Supply
Energino
Software
EPS 1
EPS 2 EPS 3
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Energino Hardware
Arduino UNO
Board
ACS712 Low
Current Sensor
Breakout
Relay Omron
G6E-134PL-ST-US
Screw Terminals
(2 Pin)
Diode
1N4001
Transistor NPN
2N3904
Arduino Stackable
Header - 8 Pin
Arduino Stackable
Header - 6 Pin
Arduino Stackable
Header - 8 Pin
Resistor
1K
Resistor
10K
Resistor
100K
Resistor
100K
USB Connector
(Standard-B Plug)
External DC
Power Supply
(7-12V)
Energino PCB
from Fritzing
Fig. 5. Energino shield on top of the Arduino UNO board [12], [16].
using amechanical relay. Thespecific features of Energino can
be found in [16]. Three Energino shields on top of Arduino
UNO boards are built following the instructions given in [16]
and redesigned in software to achieve sampling rates of 15
7.2.3 The LabView Program
In order to collect the measurements performed by Energino, it has been used a program in
developed with theLabVIEW software.
LabVIEW (Laboratory Virtual Instrument EngineeringWorkbench) isasystem-design p
and development environment for visual programming language from National Instruments
feature of LabVIEW over other development environments is the extensive support for ac
instrumentation hardware.
Theprogram developed providesan easy-to-useinterfaceto manage Energino and acqui
ples of voltage (V), current (I), and power (P) of a generic DC appliance, such as a Wi-Fi
Figure7.3isreported ascreenshoot of thevisual interfaceof theprogram. Thebehaviour of v
current and power arevisiblein Figure.
Figure7.4: TheLabView Interface
Fig. 6. Visual interfaceof thecustom-design softwarein LabVIEW
Energino [15].
general BidMAC operation considered in the analys
Figs. 7a, 7b, 7c, respectively, show the network,
average per-STA energy efficiencies of DCF and
Energino Software
Arduino UNO
Board
ACS712 Low
Current Sensor
Breakout
rew Terminals
(2 Pin)
de
001
Transistor NPN
2N3904
Arduino Stackable
Header - 6 Pin
Arduino Stackable
Header - 8 Pin
Resistor
1K
Resistor
10K
Resistor
100K
Resistor
100K
USB Connector
(Standard-B Plug)
External DC
Power Supply
(7-12V)
CB
ng
ield on top of the Arduino UNO board [12], [16].
relay. Thespecific features of Energino can
Three Energino shields on top of Arduino
7.2.3 The LabView Program
In order to collect the measurements performed by Energino, it has been used a program interface
developed with theLabVIEW software.
LabVIEW (Laboratory Virtual Instrument EngineeringWorkbench) isasystem-design platform
and development environment for visual programming language from National Instruments. A key
feature of LabVIEW over other development environments is the extensive support for accessing
instrumentation hardware.
Theprogram developed providesan easy-to-useinterfaceto manage Energino and acquiresam-
ples of voltage (V), current (I), and power (P) of a generic DC appliance, such as a Wi-Fi AP. In
Figure7.3isreported ascreenshoot of thevisual interfaceof theprogram. Thebehaviour of voltage,
current and power arevisiblein Figure.
Figure7.4: TheLabView Interface
Fig. 6. Visual interfaceof thecustom-design software in LabVIEW to con
Energino [15].
general BidMAC operation considered in the analysis.
Energino: An Energy Consumption
Monitoring Toolkit
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Summary
•Wi-Fi (IEEE 802.11 DCF MAC): Not energy efficient
•IEEE 802.11n RDP(proactive, transmitter-initiated, RD-based
protocol): outperforms DCF but is not an optimal solution
Problem
•BidMAC: reactive (receiver-initiated) RD-based protocol (i.e.,
transmit after receive) for infrastructure WLANs
•More adaptive to the actual needs of a network than RDP
Solution
•BidMAC implementation on an IEEE 802.11g WARPv3 platform
•Experimental results of energy efficiency in a proof-of-concept
network formed by an AP and 2 STAs
Contribution
•Maximum energy efficiency gains of BidMAC versus DCF:
•From 63% to 29% as the packet length grows
•From 15% to 29% as the PHY data rate increases
Result
•Improve the current BidMAC implementation by incorporating
packet aggregation and block ACK
•Evaluate the new implementation with different traffic classes
Future Work
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Thanks for your kind attention!
Fabrizio Granelli
granelli@disi.unitn.it
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MAC/PHY System Parameters*
Parameter Value Parameter Value
SIFS, DIFS, EIFS 10, 28, 88 μs ACK size 14 bytes
Slot time 9 μs MAC Header 24 bytes
Preamble 16 μs WARPv3 LLC Header 8 bytes
Signal 4 μs MSDU Size 50-1500 bytes
Signal Extension 6 μs Data Rate 6-54 Mbps
CWmin, CWmax 15, 1023 Control Rate 6,12,24 Mbps
Service 6 bits WARPv3 Power Consumption 18.95 W
Tail 16 bits Trial Time 30 s x10 times
*IEEE 802.11g MAC/PHY
The outline of the presentation is as follows. First, I will describe the problem we are focusing on. Then, I will present our solution. Finally, I will show some results of energy efficiency and energy consumption as a function of the traffic load and the data rate. But first, let me introduce the topic.
A Wireless Local Area Network (WLAN) typically consists of an access point that is usually connected to the cloud through a cable and multiple mobile devices that communicate with the access point using the same share channel. WLAN access points, also known as Wi-Fi hotspots, have been widely deployed in public and private areas, such as university campuses, business parks, and user homes. Currently, more than 3 million WLAN access point have been deployed in the world. In addition, more and more portable devices are equipped with WLAN chipsets, for instance tables, smart phones, and laptops. Now let me give you more information about that.
In these figures you can see that the number of Wi-Fi public hotspots will increase by 350% in 2015. Wi-Fi home and hotspots will contribute by 31 to 34% to overall yearly cloud energy consumption, being the second main contribution after mobile networks.
In this figure, you can see that downloading data using the WLAN interface is the second main energy consuming action in a Nokia N95. So, the wireless technologies, and not the CPU or the display, can dominate the energy consumption in some smart phones.
To address all these issues of energy consumption, we focus on the medium access control layer because it takes decisions affecting the usage of the wireless interface to regulate the access to the channel which is the main task of this layer. Because of this direction interaction with the physical layer we believe that it is the best place for energy consumption control and energy saving through cross-layer methods.
The IEEE 802.11 Standard defines the specifications of the physical and medium access control layers for WLANs.
The main limitations of DCF are the overhead generated by the exchange of control packets, silent periods, channel sensing and backoff periods, and collisions of packets.