TRUST, Spring Conference, April 2-3, 2008
Taking Advantage of Data Correlation to Control the Topology of Wireless
Sensor Networks
Sergio Bermudez and Prof. Stephen WickerSchool of ECE, Cornell UniversityTo be presented at the 15th International Conference on Telecommunications
TRUST, Spring Conference, April 2-3, 2008
Agenda
Introduction– Motivation– Background
Model and Results– Assumptions– Analysis
Conclusions
"Topology Control," Sergio Bermudez 2
TRUST, Spring Conference, April 2-3, 2008
Introduction
Application of wireless sensor network (WSN)– Power Grid– Water supply pipes
Keep nodes in place for long periods Necessity to extend their lifetime Reducing their energy consumption
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TRUST, Spring Conference, April 2-3, 2008
Motivation
Sleeping Schemes– reduce energy
consumption
Data aggregation– routing scheme with
compression of correlated data
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TRUST, Spring Conference, April 2-3, 2008
Motivation
Random Clustering– Data aggregation at cluster heads
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TRUST, Spring Conference, April 2-3, 2008
Conceptual idea
Combination of approaches to extend the network lifetime
Exploit data correlation to control the topology of a wireless network
Application to monitor physical infrastructure– Modal vibration in structures, e.g. a girder
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TRUST, Spring Conference, April 2-3, 2008
Conceptual Idea
– autonomous creation of clusters– scheduling algorithm within these clusters
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Proposed Scheme
Active nodes and backup nodes– Active nodes form the active network
Network Functional lifetime– network can carry-out useful operations
Focus on network connectivity
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TRUST, Spring Conference, April 2-3, 2008
Proposed Scheme
Two-step procedure:– Initial setup: clusters
information obtained by the correlation of the sensed data
– Organization: Sleeping Scheduling energy-efficient scheduling mechanism controls the
underlying topology of the network
Random value at deployment– Cluster formation
Random scheduling– Energy saving
"Topology Control," Sergio Bermudez 9
TRUST, Spring Conference, April 2-3, 2008
Proposed Scheme
Advantages– Localized protocol– Allows for continuous sensing
Disadvantages– Applicable in environments with strong data
correlation – Non-uniform energy depletion—secondary concern
"Topology Control," Sergio Bermudez 10
TRUST, Spring Conference, April 2-3, 2008
Assumptions
Measurements are perfectly correlated within distance tc – spatial correlation
Nodes are able to determine data correlation information
Nodes distributed according to a Poisson spatial process with intensity
High density of node platforms Boolean communication model, radius rc
Uniform energy depletion when a node is active
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TRUST, Spring Conference, April 2-3, 2008
Assumptions
Cluster Formation– Based on the spatial correlation– Define Active and Backup nodes, with
probability pa, pb
Sleeping Scheduling– Random energy-efficient scheduling mechanism
backup nodes belonging to a cluster go to sleep randomly and independently from each other
– For network robustness the backup nodes wake up periodically, with low-duty cycle
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TRUST, Spring Conference, April 2-3, 2008
Analysis: network connectivity
We get a Marked Poisson process– Active and Backup nodes, with probability pa, pb– Choose appropriate µ such that there is
connectivity with high probability
"Topology Control," Sergio Bermudez 13
~N ab pp 1
aa pN ~ bb pN ~
ANANAN ab
TRUST, Spring Conference, April 2-3, 2008
Results: network connectivity
"Topology Control," Sergio Bermudez 14
Connectivity asfunction of active nodes
Connectivity asfunction ofnode density
TRUST, Spring Conference, April 2-3, 2008
Analysis: number of neighbors
Distribution of nearest-neighbor distance
Probability that exists a backup node as a neighbor for aj
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2exp1
|1,
r
orobNPrD
c
cj
cj
jc
j
tD
tbaP
tbaP
aGPaGP
1
1
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2
1DE
TRUST, Spring Conference, April 2-3, 2008
Results: number of neighbors
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TRUST, Spring Conference, April 2-3, 2008
Results: increase in lifetime
"Topology Control," Sergio Bermudez 17
SNE
SNSNELT
a
ba
TRUST, Spring Conference, April 2-3, 2008
Conclusions
Approach to control the topology of wireless sensor networks by data correlation
Increase of functional lifetime, relevant for the monitoring of physical infrastructure
Future work:– Analysis with respect to other deployment
distribution– Couple this scheme with mobile sensor networks
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TRUST, Spring Conference, April 2-3, 2008
Further Reading
“Networking Wireless Sensors”B. Krishnamachari
“A survey of Energy-Efficient scheduling mechanisms in sensor networks”L. Wang and Y. Xiao
“The impact of spatial correlation on routing with compression in wireless sensor networks”S. Pattem, B. Krishnamachari, andR. Govindan
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