1 c-mac: model-driven concurrent medium access control for wireless sensor networks mo sha ;...
Post on 20-Dec-2015
223 views
TRANSCRIPT
1
C-MAC: Model-driven Concurrent Medium Access Control for Wireless
Sensor Networks1
1
Mo Sha ; Guoliang Xing ; Gang Zhou ; Shucheng Liu ; Xiaorui Wang
City University of Hong Kong; Michigan State UniversityCollege of William and Mary; University of Tennessee Knoxville
21
1 4
3
1 23 4
2
Outline
• Motivation
• Power control and interference models
• Design of C-MAC
• Performance evaluation
3
• Habitat monitoring, structural monitoring etc.– Sample the environment at high rates– Ex: sample @100 Hz for finding structural defect
• Limited storage capacity
• High network throughput
Data-intensive Sensing Applications
4
MACs for Wireless Sensor Nets• CSMA-based MAC protocols
– S-MAC, T-MAC, B-MAC, X-MAC…– Conservative, low throughput
• TDMA-based MAC protocols– TRAMA, DCQS, DRAND…– High maintenance overhead
• Hybrid MAC protocols– SCP, Funneling-MAC and Z-MAC – Not designed for high throughput
5
s1
r1
s2
Collision
Background of CSMA
r2
• S1: Sender 1• S2: Sender 2• R1: Receiver 1• R2: Receiver 2
Packet may be corrupted
6
s1
r1
s2
r2
Traffic Demand
Sense Channel (CCA Check)
If Channel is Clear,Transmit
Traffic Demand
Sense Channel (CCA Check)
If Channel is not Clear,Random Delay
(1)(2)
• S1: Sender 1• S2: Sender 2• R1: Receiver 1• R2: Receiver 2
Background of CSMA
7
s1
r1
s2
Collision
Is Packet Corrupted?
r2
• S1: Sender 1• S2: Sender 2• R1: Receiver 1• R2: Receiver 2
Is each packet corrupted?
8
A Case of Concurrency
s1
r1s2
r2
Power is fixed to be 15.
power increases from level 1 to 31
(1) Run1: CSMA disabled
(2) Run2: CSMA enabled
Chipcon 2420 radio;
31 tunable power levels;
256 kbps transceiver;
TinyOS-1.X.
Link 1Link 2
Tmote Sky mote
9
Experimental Result
Golden Zone:Power of Sender 1 is 15.Power of Sender 2 is between 9 and 16.
Golden Zone
10
Observations• Concurrent TXs are possible despite contention• CSMA tries avoids interference by disabling
concurrency– Back-off and channel reservation
11
Key Questions
• How to enable concurrency?– Carefully control TX power for each sender
• How to control TX power?– Empirical power control and interference models
• Power decay model• Signal-to-Interference-Noise ratio (SINR) model
12
Outline
• Application and Related Work
• Motivation
• Models• Design of MAC protocol
• Evaluation
13
• Classical exponential decay model:
Power Decay Model
RSS = P / distα
log(RSS) = log(P)- α log(dist)
14
• Experimental setup– One sender, multiple receivers at different positions– Experiments in 4 different environments
• Classical exponential decay model:
Power Decay Model
RSS = P / distα
log(RSS) = log(P)- α log(dist)
Office corridor grass field parking lot
not accurate!
15
Power Decay Model
• Near-linear RSSdBm vs. transmission power level– Overhead can be reduced
Re
ce
ive
d S
ign
al S
tren
gth
(dB
m)
Transmission Power Level
16
Pair-wise Power Decay Model
• Received signal strength (RSS) at r when s transmits with power Ps is given by
RSSr(s) = a x Ps + b
• a and b are interpolated using multiple measurements – a is estimated once– b is updated periodically
s
r
Ps
RSSr(s)
17
PRR vs. Signal-to-Interference-Noise Ratio (SINR)
• Classical model doesn't capture the gray region
office, no interfererparking lot, no interferer office, one interferer
Noise + Interference
Received Signal Strength (RSS)
0~3 dB is
"gray region"
Packet R
eception Ratio (%
)
18
Probabilistic SINR Model
• PRR(SINRi ) (1≤ i ≤ m)
PRR(0.5) PRR(1) PRR(1.5) PRR(2) …..
0 1 2 3 4 SINR (dB)
Packet R
eception Ratio (%
)
20
40
60
80
100
Classical deterministic SINR ModelOur probabilistic SINR model
20
Outline
• Application and Related Work
• Motivation
• Models
• Design of MAC protocol• Evaluation
21
Concurrency Check
InterferenceAssessment
Throughput Prediction
Data Transmission
Random Delay
Dro
pp
ed
pass
fail
max count reached
no improvement
fail
Traffic Snooping
Received Data from App
22
Concurrency Check
1. Overhear m packets (say, belonging to K links)2. For each of link uv, predict the PRR if s
transmits with min power PRRv(SNRv)
3. If the PRR of any link would drop below α (i.e., 20%), fails
RSSv(Pu)
RSSv(Psmin) + Ir+Nr
SNRv =
stored in data packet
RSSv(Psmin) = av Psmin + bv
compute from v's RSS model
compute PRRv(SNRv) from v's interference
model
23
Throughput Prediction• s tries to transmit to r• s overhears m packets (belonging to K links) • s finds power P that maximizes
• If negative, abort, otherwise transit a block of B packets
}{rKv Σ PRRv( SNRv ) – |K|
assuming 100% PRR for all active links
RSSr(P)
Interferencer+Noiser
SNRr =
obtained from handshaking
RSS model
PRR model
24
Outline
• Application and Related Work
• Motivation
• Models
• Design of MAC protocol
• Evaluation
25
Performance Evaluation• Implemented in Tmote testbed with TinyOS-1.x• 16 Tmotes deployed in a 25x24 ft office• 8 senders and 8 receivers
30
• RTS/CTS– Support data-intensive sensing applications.
• habitat monitoring [1], structural monitoring [2] and etc.
– Not for low-load applications.
Block Transmission
[1] R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler. An analysis of a large scale habitat monitoring application. In SenSys, 2004.[2] N. Xu, S. Rangwala, K. K. Chintalapudi, D. Ganesan, A. Broad, R. Govindan, and D. Estrin. A wireless sensor network for structural monitoring. In SenSys, 2004.
31
Components
ConcurrentTransmission
Engine
Power Decay Model
SINRModel
InterferenceAssessment
On
line
Mo
del E
stimatio
n
Concurrency Check
Throughput Prediction
Traffic Snooping
32
• Conflict– Senders can not concurrent transmit whatever
the sending power is, when
s1
r1
s2
r2
Multi-Channel
33
Recent studies on multi-channel
Figures in this slide are from
[1] Yafeng Wu et al, Realistic and Efficient Multi-Channel Communications in Wireless Sensor Networks, INFOCOM 2008.
34
Signal-to-Interference-Noise Ratio (SINR) model
• Classical deterministic SINR model:
Noise + Interference
Received Signal Strength (RSS)
0 1 2 3 4 SINR (dB)
Packet R
eception Ratio (%
)
20
40
60
80
100
PRR = 1 If
0 Otherwise
35
Time Sequence
Sender
Receiver
Jammer 1
Jammer n
…
syn packet
data packet
Time
RSS MeasurementsNoise Level Measurement
jam packet
Send event Receive/measure event
data packet
jam packet jam packet
jam packet
39
Related Work
• CSMA-based MAC protocols– S-MAC, T-MAC, B-MAC and X-MAC….
• TDMA-based MAC protocols– TRAMA, DCQS and DRAND…
• Hybrid MAC protocols– SCP, Funneling-MAC and Z-MAC