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Robust Topology Control for Indoor Wireless Sensor Networks. Greg Hackmann, Octav Chipara , and Chenyang Lu SenSys 2009 S S lides from Greg Hackmann at Washington University in Saint Louis. Motivation. Goal: reducing transmission power while maintaining satisfactory link quality - PowerPoint PPT Presentation
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Robust Topology Control for Indoor Wireless Sensor Networks
Greg Hackmann, Octav Chipara, and Chenyang LuSenSys 2009 S
Slides from Greg Hackmann at Washington University in Saint Louis
2
Motivation
Goal: reducing transmission power while maintaining satisfactory link quality
But it’s challenging: Links have irregular and probabilistic properties Link quality can vary significantly over time Human activity and multi-path effects in indoor networks
3
Outline
Empirical study Algorithm Implementation and evaluation Conclusion
4
Existing Empirical Studies
Many studies explore link performance at a fixed transmission power [Srinivasan 2006], [Woo 2003], [Reijers 2004], [Zhou 2004], [Lai 2003]
[Son 2004] evaluates older Chipcon CC1000 radios [Lin 2006] uses a indoor environment with line-of-sight
Our study considers 802.15.4-compliant CC2420 radios in an office environment
5
Related Topology Control Schemes
Many schemes based on theoretical radio properties [Li 2001], [Li 2005], [Blough 2006], [Gao 2008]
Power Control with Blacklisting (PCBL) [Son 2004] Collect extensive PRR (packet reception rate) data over all links at
all power levels during bootstrapping phase Statically reduce TX power on high-quality links Blacklist low-quality links
Adaptive Transmission Power Control (ATPC) [Lin 2006] Offline, compute correlation between RSSI/LQI and PRR Online, model impact of TX power at sender on RSSI/LQI at
receiver
6
RSSI & LQI
RSSI (Received Signal Strength Indicator) Remaining energy in the received signal
LQI (Link Quality Indicator) CC2420 radio provides LQI following 802.15.4 standard Can accurately reflect the packet error rate (PER) of a channel, if
measured for 100 packets
7
Advantages of Topology Control Testbed Topology
0 dBm-15 dBm-25 dBm
8
Is Per-Link Topology Control Beneficial?
Impact of TX power on PRR
3 of 4 links fail @ -10 dBm ...
... but have modest performance @ -5 dBmInsight 1: Transmission power should be set on a per-
link basis to improve link quality and save energy.
9
What is the Impact of Transmission Power on Contention?
Highcontention
Low signal strength
Insight 2: Robust topology control algorithms must avoid increasing contention under heavy network load.
10
Is Dynamic Power Adaptation Necessary?
Link 110 -> 139
11
Can Link Stability Be Predicted? Long-Term Link Stability
Insight 3: Robust topology control algorithms must adapt their transmission power in order to maintain
good link quality and save energy.
12
Are Link Indicators Robust Indoors?
Two instantaneous metrics are often proposed as indicators of link reliability: Received Signal Strength Indicator (RSSI) Link Quality Indicator (LQI)
Can you pick an RSSI or LQI threshold that predicts whether a link has high PRR or not?
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Are Link Indicators Robust Indoors? Links 106 -> 129 and 104 -> 105
RSSI threshold = -85 dBm, PRR threshold = 0.9
4% false positive rate62% false negative rate
RSSI threshold = -84 dBm, PRR threshold = 0.9
66% false positive rate6% false negative rateInsight 4: Instantaneous LQI and RSSI are not robust
estimators of link quality in all environments.
14
Summary of Insights
1. Set transmission power on a per-link basis2. Avoid increasing contention under heavy network load3. Adapt transmission power online4. LQI and RSSI are not robust estimators of link quality in all
environments
15
Adaptive and Robust Topology control (ART)
ART:1. Adjusts each link’s power individually 2. Detects and avoids contention at the sender3. Tracks link qualities in a sliding window, adjusting
transmission power at a per-packet granularity4. Does not rely on LQI or RSSI as link quality estimators
5. Is simple and lightweight by design 392 bytes of RAM, 1582 bytes of ROM, often zero network
overhead
16
ART Algorithm Outline
TRIAL
Trying a lowerpower
INITIALIZING
Packet windowfilling
STEADY
Link quality withinthreshold
Packet window full
Link quality abovethreshold
Link quality goes back below threshold
Link quality fallsbelow threshold
Link quality
stays
at/above threshold
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Avoiding Contention
Naïve policy: When link quality falls below threshold, then increase power level
But what if this makes things worse? Remember, higher power → more contention
Initially increase power when link quality is too low, but remember how many failures were recorded in window
If # of failures is worse than last time, then flip direction and decrease power instead
18
Implementation Details
Implemented using TinyOS 2.1 CVS on top of the MAC Layer Architecture [Klues 07]
Sits below routing layer -> has been tested with Collection Tree Protocol [Gnawali 2008]
Deployed on Jolley Hall testbed for three experiments: Link-level High contention Data collection (not presented here)
19
Link-Level Performance
Selected 29 links at random from 524 detected in empirical study
Transmitted packets round-robin over each link in batches of 100, cycled for 24 hours (15000 packets/link)
PRR Avg. Current
Max Power 56.7% (σ = 2.5%) 17.4 mA (σ = 0)ART 58.3% (σ = 2.1%) 14.9 mA (σ =
0.32)
20
Handling High Contention
Select 10 links at random from testbed Send packets over all 10 links simultaneously as possible
(batches of 200 packets for 30 min.)
Compare again against PCBL and max-power Also run ART without “gradient” optimization to isolate its
effect on PRR
21
Handling High Contention Packet Reception Rate and Energy Efficiency
Max-Power PCBL ART ART (w/o gradient)0
0.2
0.4
0.6
0.8Pa
cket
Rec
eptio
n Ra
te
Max-Power PCBL ART ART (w/o gradient)0
0.2
0.4
0.6
0.8
1
Nor
mal
ized
Cos
t of
One
Goo
d Pa
cket
50.9% moreenergy efficientthan max-power
40.0% moreenergy efficientthan max-power
22
Handling High Contention Distribution of PRR
0 0.050.10.150.20.250.30.350.40.450.50.550.60.650.70.750.80.850.90.95 10
0.10.20.30.40.50.60.70.80.9
1
Max-Power PCBLART ART (w/o gradient)
Packet Reception Rate
CDF(
Pack
et R
ecep
tion
Rate
)
23
Conclusions
Our empirical study shows important new negative results: RSSI and LQI are not always robust indicators of link quality
indoors Profiling links even for several hours is insufficient for identifying
good links Inherent assumptions of existing protocols!
ART is a new topology control algorithm which is robust in complex indoor environments
ART achieves better energy efficiency than max-power without bootstrapping or link starvation