2M. Baqer [email protected]
Outline • Sensor Networks• Energy Conservation• Patterns and Sensor Networks• Application• So What’s the Big Deal? • Challenges of Event Recognition in Sensor Networks• Event Recognition for Sensor Networks• Voting Graph Neuron• VGN Model• Voting and Consensus• Sleeping Mode• Example• SGSIA• Summary
3M. Baqer [email protected]
Sensor Networks
• Random vs. deterministic deployment• Long term deployment• Dynamic infrastructure• Unattended operations• Scale
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Energy Conservation
• Scheduling-based– Operation mode (transmitting, receiving,
idle, sleeping)
• In-network Processing-based– Aggregation
– Compression
– Beamforming
– CSIP
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Patterns and Sensor Networks
• Spatio-temporal event patterns• Pattern collection
– continuously
– periodically
– Even-driven
– User-driven
– hybrid
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Application: Structural Health Monitoring
• SHM replace visual inspection
• Applied for– Predict– Detect– monitor
structures for damages
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So, What’s the Big Deal?
• Can’t centralised servers (base station / sink node) perform pattern recognition for sensor networks?– Geographically dispersed sensory data
– Require global information
– Communication overhead
– Offline detection
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Challenges of Event Recognition in Sensor Networks
• Global vs. local• Constraint resources• Dynamic infrastructure• Energy efficiency• Scalable
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Event Recognition for Sensor Networks
• Template matching• Distributed artificial intelligence• Cooperative distributed problem solving
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VGN algorithm
• Votes vectors:– Local match
• Use:– Local processing, information exchange and
decision fusion
• Consensus– Cooperatively negotiating by casting votes
– Cast and rebuild vote vectors
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Sleep Mode
• Committee members enter into sleep mode to conserve their energy
• Who may go into the sleep mode?– Committee members that already cast their vote
– Committee members with identical votes
• When do identical vote vectors get created?– Initialisation stage
– Negotiation stage
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Example
Input sensory pattern Committee negotiation process
Colour map of the negotiation process
14M. Baqer [email protected]
Comparison results of the difference in the pattern matching performance for committee storing random patterns and alphabet character patterns
15M. Baqer [email protected]
SGSIA
• In-network Data Processing for Secure Grid-Sensor Integration Architecture
• Provide timely and accurate responses to data acquisition requests intended for WSNs
• Data processing at the sensor nodes to filter raw sensory data
• Optimal and selective forwarding of grid-generated queries to the appropriate sensor networks.
• Grid proxy: interface, QoS, cashing
• Gateway (base station): managing, fuse, translate
17M. Baqer [email protected]
Summary
• Ambient intelligence• Decentralised in-network pattern
recognition• Scalability• Adaptability