Mobile Computing: Wireless Mesh and Sensor

NetworksThomas Kunz

Professor and Director

Technology Innovation Management Program

Carleton University

Slide Kunz

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

Slide Kunz

Wireless Mesh Networks

(Microsoft Research Video Clip)

Slide Kunz

Wireless Mesh Testbed

Slide Kunz

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

Slide Kunz

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

Slide Kunz

(Wireless) Sensor Networks (Scenario developed by RUNES project: http://www.ist-runes.org/)

Slide Kunz

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

Slide Kunz

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

Slide Kunz

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

Slide Kunz

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.