Transcript GeneralDynamics - Carleton University

Mobile Computing:
Wireless Mesh and Sensor
Networks
Thomas Kunz
Professor and Director
Technology Innovation Management Program
Carleton University
Mobile Computing Group at Carleton
 Facilitate the development of innovative next-generation mobile
applications on resource-constraint, mobile devices
 Develop the required network architectures (MANETs, wireless
mesh networks, wireless sensor networks)
 Research into network protocols (MAC, routing, Mobile IP, QoS
support, transport), and middleware/runtime support
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Wireless Mesh Networks
(Microsoft Research Video Clip)
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Wireless Mesh Testbed
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Wireless Mesh Testbed (cont)
 Mesh routers: IXP 425 based nodes with two radios
– Provide local footprint/soft AP functionality to clients over one radio
– Use second radio for building IPv6 based mesh: OLSR routing protocol with QoS
extensions
 Mesh testbed built with close collaboration from one small Ottawa
startup
 Some routing work licensed to another Ottawa company and being
productized in their Adaptive Intelligent Router offering
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Current Wireless Mesh Research
 Capacity and Fairness:
– WMN shared resource for all users
– WMN have finite (and rather limited) capacity to support a number of users
– Goal: maximize utilization of network while providing “fair” access to all users
 Analytical performance bounds
 Distributed algorithms/protocols
 Definition of “Fairness”
 Tradeoff Fairness vs. Utilization
 Generating Routing Protocols “automatically” using Generative
Programming approach: GP-Pro
 Network Management for Dynamic Networks
– Maritime Network: Policy-based Network Management
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(Wireless) Sensor Networks
(Scenario developed by RUNES project: http://www.ist-runes.org/)
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WSN Research
 Developed new localization and clock synchronization algorithms
 Currently setting up a WSN testbed (jointly with Prof. St-Hilaire)
 Ongoing research:
– Evaluate above algorithms in testbed, extend them
– Capacity in multi-hop wireless networks (network coding)
– Security: bootstrapping trust without prior configuration
– Application-oriented overlay networks
 XML Aware Wired Networks/World Wide Sensor Web
– Model, discover, and interact with distributed sensors based on XML standards
– efficient distribution of different information derived from the sensors to various
interested parties (first responders, airport authorities, etc.): content-based routing
– combine/fuse data derived from different sites
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SENECA: Sensor Networks for Canada
 Proposed NSERC Strategic Network
– 7 Canada Research Chairs, 3 other researchers from UQO, University of Ottawa, University of
Sherbrooke, Ecole Polytechnique, Carleton University, ISMER, Concordia
– Partners: End users (CATSA, CBSA, EC), manufacturers (Fiso, Biophage Pharma, Enablence,
IR Photonics, ….)
– Goal: Hybrid integration of photonics-based sensors and wireless networking
– Structured around three themes
 Application-specific Sensor Communication and Integration Technologies
 Application-Specific Photonic Devices and Subsystems
 Enabling Photonic Materials, Fibers and Processing Technologies
– Selected Applications for Wide Area Photonic and Wireless Sensing
 remote detection of explosive materials and biological hazards
 measure nutrient and contaminant concentrations in water
 geo-fencing solutions to protect critical infrastructure
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Prof. St.-Hilaire: Wireless Sensor Networks (WSN)
 Research in planning algorithms (both static & dynamic)
– How to design new WSN in a cost effective way
– How to update an existing WSN infrastructure
– Organisation (re-organisation) of the nodes to maximize the life time of the network
 Research on network protocols
– Routing scheme with different objectives
 Save energy, minimise delay or combination
 Re-organise the route in case of node/link failure
– Correlation of events both in space and time
 Clock synchronisation
 Localization algorithm
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Prof. St.-Hilaire: Wireless Sensor Networks (WSN)
 Research on data association
– How to follow multiple moving targets such as in military applications, border
defence and so on.
 Research on data aggregation/fusion
– Aggregate data in order to save bandwidth, computing resources, battery life, etc.
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