Presentations by myself

Website:

• Website:

• http://rabieramadan.org/classes/2012/sensor/

• Presentations by myself

• Assignments

• Some other materials will be provided

• Introduction and Basic Concepts

Most of the traditional wireless networks occur over fixed infrastructure

• Most of the traditional wireless networks occur over fixed infrastructure

• Access points

• Many wireless protocols (heterogeneity problem)

• Bluetooth, WiFi, WiMax

• We need Seamless network

• Connects everyone from their home to work,..

• Disasters may be a drive force for such networks

Wireless Cellular Networks

• Wireless Cellular Networks

• First , Second, 2.5 , third, and 4th generations

• Wireless Ad Hoc Networks

• Nodes function as host and router
• Dynamic topology
• Nodes may departure
• Requires efficient routing protocols
• Mobile Ad Hoc Networks (MANET)
• Wireless Sensor Networks (WSN)

Sensing:

• Sensing:

• Is a technique used to gather information about a physical object or process, including the occurrence of events (i.e., changes in state such as a drop in temperature or pressure).

• Sensor:

• An object performing such a sensing task
• Converts energy of the physical worlds into electrical signal.
• Sometimes named “Transducer”  converts energy from one form to another.

• Examples on remote sensors:

• Nose, ears, and eyes  They do not need to touch the monitored objects to gather information

PIR is a differential sensor: detects target as it crosses the “beams” produced by the optic

• PIR is a differential sensor: detects target as it crosses the “beams” produced by the optic

Data Collection

• Data Collection

• In-Network Analysis

• Data Fusion

• Decision Making

Types of Measured Phenomena

• Types of Measured Phenomena

Defense Advanced Research Projects Agency (DARPA) organized the Distributed Sensor Nets Workshop (DAR 1978).

• Defense Advanced Research Projects Agency (DARPA) organized the Distributed Sensor Nets Workshop (DAR 1978).

• DARPA also operated the Distributed Sensor Networks (DSN) program in the early 1980s,

Rockwell Science Center, the University of California at Los Angeles proposed the concept of Wireless Integrated Network Sensors or WINS.

• Rockwell Science Center, the University of California at Los Angeles proposed the concept of Wireless Integrated Network Sensors or WINS.

• One outcome of the WINS project was the Low Power Wireless Integrated Microsensor (LWIM), produced in 1996

The Smart Dust project at the University of California at Berkeley focused on the design of extremely small sensor nodes called motes. (year of 2000).

• The Smart Dust project at the University of California at Berkeley focused on the design of extremely small sensor nodes called motes. (year of 2000).

• The goal of this project was to demonstrate that a complete sensor system can be integrated into tiny devices, possibly the size of a grain of sand or even a dust particle.

Crossbow (www.xbow.com),

• Crossbow (www.xbow.com),

• Sensoria (www.sensoria.com),

• Worldsens (http://worldsens.citi.insa-lyon.fr),

• Dust Networks (http://www.dustnetworks.com ), and

• Ember Corporation (http://www.ember.com ).

Energy

• Energy

• Sensors powered through batteries sometimes impossible to do.
• Mission time may depend on the type of application (e.g. battlefield monitoring – hours or days)
• Node’s layers must be designed carefully.

Responsible for providing sensor nodes with access to the wireless channel.

• Responsible for providing sensor nodes with access to the wireless channel.

• Responsible of Contention free Transmission .

• MAC protocols have to be contention free as well as energy efficient.

• Contention free requires listening to the wireless channel all the time
• Energy efficient requires turning off the radio

Responsible for finding routes from a sensor node to the base station

• Responsible for finding routes from a sensor node to the base station

• Route characteristics such as length (e.g., in terms of number of hops), required transmission power, and available energy on relay nodes

• Determine the energy overheads of multi-hop communication and try to avoid it.

Energy affects the O.S. design :

• Energy affects the O.S. design :

• Small memory footprint,
• Efficient switching between tasks
• security mechanisms

Self-Management

• Self-Management

• Sensors usually deployed in harsh environment.
• There is no pre-infrastructure setup.
• Once deployed, must operate without human intervention
• Sensor nodes must be self-managing in that
• They configure themselves,
• Operate and collaborate with other nodes,
• Adapt to failures, changes in the environment,

Self-organization

• Self-organization

• A network’s ability to adapt configuration parameters based on system and Environmental state.

• Self-optimization

• A device’s ability to monitor and optimize the use of its own system resources

• Self-protection

• Allows a device to recognize and protect itself from intrusions and attacks

• Self-healing

• Allows sensor nodes to discover, identify, and react to network disruptions.

Deterministic Vs. Ad Hoc Deployment

• Deterministic Vs. Ad Hoc Deployment

Wireless Networking

• Wireless Networking

• Transmission Media
• Sensors use wireless medium
• Suffer from the same problems that wireless networks suffer from
• Fading
• High error rate

Wireless Networking

• Wireless Networking

• Communication range
• Communication ranges are always short
• It is required for the network to be highly connected
• Routing paths will be long
• What about critical applications where delay is not acceptable
• QoS will be an issue

Wireless Networking

• Wireless Networking

• Sensing Range
• Very small
• Nodes might be close to each other
• Data Redundancy

Decentralized Management

• Decentralized Management

• Requires Distributed Algorithms
• Overhead might be imposed

• Security

• Exposed to malicious intrusions and attacks due to unattendance characteristics.
• denial-of-service
• jamming attack

Dense Node Deployment

• Dense Node Deployment

• Battery-Powered Sensors

• Sever Energy , Computation , and Storage Constraints

• Self Configurable

• Application Specific

• Unreliable Sensor Nodes

• Frequent Topology Change

• No Global Identifications

• Many-to-One Traffic pattern ( multiple sources to a single Sink node)

• Data Redundancy

Fault Tolerance

• Fault Tolerance

• Large number of nodes already deployed or
• Nodes do the same job. If one fails , the network still working because its neighbor monitors the same phenomenon .

• Mobility

• Helps nodes to reorganize themselves in case of a failure of any of the nodes

• Attribute-Based Addressing

• Addresses are composed of group of attribute-value pairs
• Ex. < temp > 35, location = area A>

Location Awareness

• Location Awareness

• Nodes’ data reporting is associated with location

• Priority Based Reporting

• Nodes should adapt to the drastic changes in the environment

• Query Handling

• The sink node / user should be able to query the network
• The response should be routed to the originator
• We might have multiple sinks in the network

Micro-Electro-Mechanical Systems

• Micro-Electro-Mechanical Systems

• (MEMS) is a core technology that:

• Leverages IC fabrication technology
• Builds ultra-miniaturized components
• Enables radical new system applications

Augmented General Purpose PCs

• Augmented General Purpose PCs

• Embedded PCs (PC104), PDAs, etc..
• Usually have O.S like Linux and wireless device such as Bluetooth.

• Dedicated Sensor Nodes

• Commercially off the shelf components (e.g. Berkeley Motes)

• System-on-chip Sensor

• Platform like Smart dust, BWRC PicoNode

Operating Systems and Language Platforms

• Operating Systems and Language Platforms

• Typical Platforms are:

• TinyOS, nesC, TinyGALS, and Mote

• TinyOS

• Event Driven O.S.
• Requires 178 bytes of memory
• Supports Multitasking and code Modularity
• Has no file system – only static memory allocation
• Simple task scheduler

• nesC – extension of C language for TinyOS- set of language constructs

• TinyGALS - language for TinyOS for event triggered concurrent execution .

• Mote’ - Virtual machine for Berkeley Mote

IEEE 802.15.4 Standard

• IEEE 802.15.4 Standard

• Specifies the physical and MAC Layers for low-rate WPANs
• Data rates of 250 kbps, 40 kbps, and 20 kbps.
• Two addressing modes: 16 - bit short and 64 - bit IEEE addressing.
• Support for critical latency devices, for example, joysticks.
• The CSMA - CA channel access.
• Automatic network establishment by the coordinator.
• Fully handshaking protocol for transfer reliability.
• Power management to ensure low - power consumption.
• Some 16 channels in the 2.4 - GHz ISM band, 10 channels in the 915 – MHz band, and 1 channel in the 868 - MHz band.

IEEE 802.15.4 Standard

• IEEE 802.15.4 Standard

• The physical layer is compatible with current wireless standards such as Bluetooth
• MAC layer implements synchronization , time slot management , and basic security mechanisms.

Border Monitoring:

• Border Monitoring:

• Detect movement where none should exist ,

• Decide target classes, e.g., foot traffic to tanks

• Ideal when combined with towers, tethered balloons, or UAVs

Sensors HW and Software

• Sensors HW and Software

• Deployment

• Physical , MAC, Routing, Applications

• Data Aggregation and Data Mining

• Artificial Intelligence and data handling

• Self Healing

• Web Integration

• Heterogeneity

• Security

• Software Engineering (Simulators )

• Cloud Computing and Sensor Networks

• Mobility Issues and Localization

Your assignment is to read one sensor network application, as reported in a published paper. Surf the web to find material complementary to my pointers.

• Your assignment is to read one sensor network application, as reported in a published paper. Surf the web to find material complementary to my pointers.

• Prepare a presentation for only 15 minutes ; use the model of this power point presentation presentApp.ppt.

• Before next class, you'll need to email me your presentation.

• Your presentation will let other students know about some sensor network application, so they have an overview without having to read the paper in as much detail as you did.

• To prepare the presentation, you likely need’nt master all the details of the paper. Often, though, it can help to find backup technical reports and presentations by the researchers, to help you prepare. Overall, you should spend about four to six hours on this task.

• Your presentation will be posted on the website to be read by others and it is part of our class . Be ready for some questions from your classmates or from the instructor

Hospital Epidemiology: Wireless Applications for Hospital Epidemiology [ref]

• Hospital Epidemiology: Wireless Applications for Hospital Epidemiology [ref]

• Nericell: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones [ref]

• Participatory sensing in commerce: Using mobile camera phones to rack market price dispersion [ref]

• The BikeNet Mobile Sensing System for Cyclist Experience Mapping [ref]

• Model-Based Monitoring for Early Warning Flood Detection [ref]

• NAWMS: Nonintrusive Autonomous Water Monitoring System [ref]

• Luster: Wireless Sensor Network for Environmental Research [ref]

• Hybrid sensor network for cane-toad monitoring [ref]

• SensorFlock: An Airborne Wireless Sensor Network of Micro-Air Vehicles [ref]

• Identification of Low-Level Point Radiation Sources Using a Sensor Network [ref]

Mobile Sensor/Actuator Network for Autonomous Animal Control [ref]

• Mobile Sensor/Actuator Network for Autonomous Animal Control [ref]

• Detecting Walking Gait Impairment with an Ear-worn Sensor [ref]

• Textiles Digital Sensors for Detecting Breathing Frequency [ref]

• Recognizing Soldier Activities in the Field [ref]

• Physical Activity Monitoring for Assisted Living at Home [ref]

• PipeNet: Wireless sensor network for pipeline monitoring [ref]

• Turtles At Risk [ref]

• Cyclists' cellphones help monitor air pollution [ref]

• Clinical monitoring using sensor network technology [ref]

• CargoNet: low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive asychronous monitoring of exceptional events [ref]

• Monitoring persons with parkinson's disease with application to a wireless wearable sensor system [ref]

Expressive footwear, shoe-integrated wireless sensor network [ref]

• Expressive footwear, shoe-integrated wireless sensor network [ref]

• BriMon: a sensor network system for railway bridge monitoring [ref]

• Monitoring Heritage Buildings [ref]

• PermaDAQ: gathering real-time environmental data for high-mountain permafrost [ref]

• Firewxnet: a multi-tiered portable wireless for monitoring weather conditions in wildland fire environments [ref]

• Development of an in-vivo active pressure monitoring system [ref]

• Personal assistive system for neuropathy [ref]

• Smart jacket design for neonatal monitoring with wearable sensors [ref]

Condition Monitoring in Intel Hillsboro Fabrication Plant

• Condition Monitoring in Intel Hillsboro Fabrication Plant

• or BP’s Loch Rannoch Oil Tanker [ref]

• Other BP applications (safety, corrosion detection, empty propane tanks)

• Volcano Monitoring

• Seismic Monitoring

• Landslide Detection

• Water Distribution Monitoring and Control (agricultural and sewer)

• Water Quality

• Water Sense

• Lake (Aquatic organism) Monitoring

• Cane Toad Monitoring

• Neptune Ocean Observatory [ref]

• Atmospheric Observatory [ref]

• Neon (scope and canonical experiments)

SensorScope

• SensorScope

• SenseWeb

• CarTel [ref]

• Odor Source Localization

• CodeBlue (Health care)

• Activity Recognition [ref]

• Assisted Living [ref]

• Wearable wireless body area networks (Health care)

• Adaptive house

• PlaceLab and House_n projects

• Participatory Sensing

• Responsive Environments (Uberbadge)

• Lover’s cup context aware

SensorWebs in the Wild

• SensorWebs in the Wild

• Dynamic Virtual Fences for Controlling Cows

• Hardware design experiences in ZebraNet

• Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet (see also additional background & Zebranet Web Site)

• Sensor/actuator networks in an agricultural application (you'll need to search for more on this topic)

• http://www.tde.lth.se/cccd/images/CCCD%20Workshop%202004-JMadsen.pdf
• www.diku.dk/users/bonnet/papers/PhB-Kuusamu.ppt

• Smart-Tag Based Data Dissemination

• Sensor network-based countersniper system

• A large scale habitat monitoring application

• Wireless Sensor Networks for Habitat Monitoring.
• Habitat Monitoring: Application Driver for Wireless Communications Technology.
• Preprocessing in a Tiered Sensor Network for Habitat Monitoring
• Wireless Sensor Networks for Habitat Monitoring
• Additional Sensor Network Project Sites: Coastal Observatory, Santa Margherita Reserve, Rockwell: Surveillance, Great Duck Island

Dynamic Networking and Smart Sensing Enable Next-Generation Landmines

• Dynamic Networking and Smart Sensing Enable Next-Generation Landmines

• Flock Control

• Adaptive Sampling Algorithms for Multiple Autonomous Underwater Vehicles, Proceedings IEEE Autonomous Underwater Vehicles Workshop Proceedings, Sebasco, ME, June, 2004

• Sensor Web for In Situ Exploration of Gaseous Biosignatures

• Active visitor guidance system (follow the single reference, using Google, to find more)

• Two-Tiered Wireless Sensor Network Architecture for Structural Health Monitoring

• Sensor-actuator network for damage detection in civil structures

• Meteorology and Hydrology in Yosemite National Park: A Sensor Network Application.

• A Survey of Research on Context-Aware Homes.

• The Aware Home: A Living Laboratory for Ubiquitous Computing Research
• Using Pervasive Computing to Deliver Elder Care

• Workplace Applications of Sensor Networks

• Cougar Project at Cornell (student projects, which have some slides about a demo)

• Contaminant Transport Monitoring

• Marine Microorganisms   (Adaptive Sampling for Marine Microorganism Monitoring)

• A Support Infrastructure for the Smart Kindergarten