segal’s law
DESCRIPTION
Segal’s Law. A man with a watch knows what time it is. A man with two watches is never sure. A Decentralized Frame Synchronization of a TDMA-based Wireless Sensor Network. Fasika Assegei Advisors: Frits van der Wateren – Chess B.V. dr.ir. Peter Smulders – TU/e. - PowerPoint PPT PresentationTRANSCRIPT
Fasika Assegei
Segal’s Law
A man with a watch knows what time it is.
A man with two watches is never sure.
http://www.chess.nlFasika Assegei
A Decentralized Frame Synchronization of a TDMA-based
Wireless Sensor Network
Fasika Assegei
Advisors: Frits van der Wateren – Chess B.V. dr.ir. Peter Smulders – TU/e
Fasika Assegei
This research is ….
DevLab project
a project to build a functional WSN for research on protocols, power management, programming models, and security.
What is MyriaNed ?
• Conducted at Chess B.V. in Haarlem , the Netherlands
• Part of MyriaNed project
Fasika Assegei
Outline of presentation
Synchronization in Wireless Sensor Networks
What is wrong with Median algorithm ?
Proposed algorithms
Energy and its conservation
Simulation Results
Conclusion and future work
Fasika Assegei
Why synchronization?
TDMA Slots
Data Integration
NTP
Having the same notion of time
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Isn’t this a solved problem by now ??? NTP, MACs with sync built in (802.11), time broadcasts (GPS,
WWVB), high-stability oscillators (Rubidium, Cesium)
New problems arise in Wireless Sensor Networks Important assumptions no longer hold
(fewer resources -- such as energy, good connectivity, infrastructure, size, and cost -- are available)
Sensor apps have stronger requirements (…but we have to do better than the Internet anyway)
What now ?
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Wireless Sensor Networks: Why different ?
Energy limitation Each node has a limited battery life
Dynamic nature of the network, as well as inaccessibility Mobility and interference
Diverse applications Relative and absolute reference
Cost of node Cheap node
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Synchronization Methods- Previously
Centralized synchronization Central reference time Global or Relative
Receiver-Receiver RBS ( Receiver Broadcast Synchronization)
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Synchronization Methods- Previously
Decentralized synchronization Estimation of the other’s clock time
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What is NEW here ?
Decentralized synchronization Relative time references
No time stamping Low message overhead and no sync message
Primarily using estimation (biased and unbiased)
Energy efficient Able to use as low energy as possible
Unnecessary synchronization wastes energy, and insufficient synchronization leads to poor performance.
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Definitions
Phase error Time difference between the clocks
Frequency error The difference in the rates of the
clocks
Clock cycle (clk) The time between adjacent pulses of
the oscillator
Wake-up time The time that the node starts to listen
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Sources of Error
Oscillator characteristics: Accuracy: Difference between ideal frequency and
actual frequency of the oscillator. Stability: Tendency of the oscillator to stay at the same
frequency over time.
Network and System Parameters Receive and Transmit Delay: Time duration between
message generation and network injection. Propagation Delay: Time to travel from sender to
receiver. Access Delay: Time to access the channel.
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Clock drift
1)(
1dt
tdC
The nodes clock time is thus bounded as :
where ρ is the maximum clock drift.
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Synchronization algorithms
Synchronization Parameter Space:(max error, lifetime, scope, convergence,
stability)
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Synchronization frequency
T
Tt syncdiff 2
xguardslot Ttt
1T
Tsync
The period in which the network can stay synchronized without the application of the synchronization algorithm.
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)()()( nj
ni
nij ttt
io
n
ni
ni tTt )()(
)()()1( ni
ni
ni
ni Ttt
)( )()( nij
ni tf
Mathematical Model
What is f ???
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Median as a method for synchronization
Very simple method.
Calculates the Median of the phase errors
Adjusts the offset in the next wakeup time of the node.
With the simplicity, comes the price……
Not stable in a highly dynamic networks.
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What is wrong with Median ?
Got message from Node 3Calculating
offset
Got message from Node 10
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Node 9 drifted from
its neighbors
A WSN scenario for Median contd.
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)()()1( ni
ni
ni
ni Ttt
N
j
nijij
ni
ni
ni twTtt
0
)()()()1(
N
j
njij
ni
ni twTt
0
)()()1(
Weighted measurements
ijw,1 ij
,ij
Weight selection : two steps in determining the weight factor
Offset calculation:
5.0)( ijmean
5.0)( ijmean .1ijwwhere
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Weighted Measurements Contd.
)()1( nij
nij ww
ijtbij ae
The larger the phase error is, the lower the value it is assigned.
Fasika Assegei
)log(),( 21 ii xxf
),)...(,(),,(),,( 332211 nn yxyxyxyx
n
iirS
1
2
),( iii xfyr
jkj
kj 1
j
iij
rJ
yJJJ Tj
T )(
Non Linear Least Squares Contd.
Set of data points :
Squares of error :
where:
Iteration of parameters:
where:
Non Linear Least Squares - Curve:
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Non Linear Least Squares approach
Upper bound is the synchronization error to be permitted….
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Discrete time kalman filter
Kalman filter estimates a process by using a form of feedback
control the filter estimates the process state at some time
then obtains feedback in the form of (noisy) measurements.
Predict equations
Update equations
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1
0lim
HKk
Rk0lim
0
kP
Kk
Kalman Filter Contd.
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Reducing the duty cycle ……..
xslot TxT 2
T
NTD slot
T
TxND x )2(
T
TxND x
n
))(2(
T
ND
)2( A decrease in the duty cycle:
For a performance improvement:
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Simulation setup
Mixim Octave
Input
Output
Discrete Event Simulation
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Abstraction
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Simulation results
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Simulation results Contd.
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Simulation results Contd.
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Simulation results Contd.
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Simulation results
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Simulation results Contd.
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Simulation results Contd.
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Simulation results Contd.
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Active Idle Sleep
CPU 3.5mA 0.01mA 5μA
Radio 11.3mA(TX) 12.3mA 5μA
Radio 12.3mA(RX) 12.3mA 5μA
Tradeoff? Directly comparing computation/communication energy cost not
possible but: put them into perspective! Energy ratio of “listening for 1 clk ” vs. “computing one instruction
per cycle”: In the range of 5 to 10 times Try to compute instead of communicate whenever possible
Communication is more expensive than computing.
Computation vs. communication energy cost
900 mAh
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Energy Consumption
Battery life of a MyriaNode vs Guard time
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Conclusion
A decentralized synchronization for a TDMA-based WSN algorithm is proposed using KF, WM and NLLS.
WM and NLLS have a better tolerance to the dynamic nature of Wireless Sensor Network.
KF performs the best in all synchronization space, both in static as well as dynamic environments.
Median is still the choice in static environment, when considered in all aspects (energy and performance).
Reducing the communication cost and increasing cost of computing is worthy bait.
Fasika Assegei
Future work
Software power minimization techniques to reduce the power consumption of the algorithms.
Implementation of the algorithms on the MyriaNode and further investigation for perfection.
Additional tools for frequency error minimization, using the available resources.
More advanced estimation techniques and low power implementation.
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Thank you!
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What causes the clock to drift ?
The frequency of the clock is given as :
a is the aging factor fe is the environmental factor (temperature..) fr is the noise instability
fo is the nominal frequency
)()()()( 0 tftfttaftf reo
where :
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Lower bound of synchronization
where n is the number of nodes in the network. This means that synchronization is not only a local
property, in the sense that the clock skew between two nodes depends not only on the distance between the nodes
but also on the size of the network.
))1log()1(8
log(
)1log(
)1(8
n
ndL
Fasika Assegei
What is synchronization ?
Having the same time of reference and count the same time [either global (UTC) or local (relative)]
Operate a system in unison
Same notion of time
We are synchronized!!!!
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Wireless Sensor Networks
Wireless network of low cost sensors. Nodes communicate by broadcasting. Multihop communication needed in order to reach
far-away destinations.