sensor net

Large scale sensor networks are only recently emerging with a large spectrum of applications .

Distributed relaying will be shown to decrease the power consumption per relaying sensor node.

Figure 12: Distributed relaying sensor network for fire detection in forests.

© 2003 –2004 by Yu Hen Hu 3

Smart sensors

Transducers

Power

On-board processor, storage

Wireless transceivers

Ad hoc network

No predefined, fixed network configuration

Transmit, receive, and relay information

Wireless communication

Radio, infrared, optical, and other modalities

Vision Smart environment:

▪ Monitoring▪ Control, interaction

Large number of low cost sensor nodes deploy-n-play, self-configuration to form network, Collaborative in-situ information processing

Applications Environmental monitoring Civil structure/earth quake

monitoring Premises security Machine instrument diagnosis Health care

wireless sensor prototype by Wang et al. (2005).

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Wireless Sensor Networks

Sensing and Processing Unit

Wireless Transceiver

Ad Hoc Network Topology

Battlefield surveillance, disaster relief, border control, environment monitoring, … etc.

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1,1x

Manager node

2,1x 1,2x 2,2x

1,3x 2,3x

• Data fusion– Feature vectors from different node

measurements are combined – Higher computational burden since

higher dimensional (vector) data is jointly processed

– Higher communication burden– Larger training data requirement

1,1x

Manager node

2,1x 1,2x 2,2x

1,3x 2,3x

• Decision fusion– Decisions (hard or soft) based on

node measurements are combined – Lower computational burden since

lower dimensional data (scalar decisions) is jointly processed

– Lower communication burden– Lower training data requirement

Two Extremes

destination

Code and communicate all data to a central point for processing and analysis

Local processing and communication between nodes; communicate result to central point

data estimate

destination

Physical Limitations

Low density network

• low bandwidth/energyconsumption

• low spatial resolution

High density network

• high bandwidth/energyconsumption

• high spatial resolution

Key Questions

How dense should we sample ?

What are the transmission rate limitationsfor a given network density ?

What are the energy/power requirementsfor a given network density ?

What accuracy is achievable under bandwidthand energy constraints ?

Signal + Noise Model

noiseless field noisy sensor measurements

1. D(n): Achievable accuracy using n sensors ?

2. E(n): Energy required to transmit data or estimates ?

3. How do accuracy and energy scale with node density ?

MSE-Energy Analysis

higher density

higher resolutionmore averaging

higher density

more datamore communication

Ex: Estimating a Piecewise Constant Field

Estimation

n sensorseach makes a noisymeasurement of thefield at its location

(e.g., each contaminatedwith Gaussian noise)

Energy and Communication

Goal: transmit a goodestimate of field to upperleft corner via multi-hop communication

Hierarchical Comm and Data Processing

• hierarchical pyramid structure for sensor networkcomm and data handling (Ganesan, Estrin, Heidiman ’02

Madden et al ’02, Hellerstein et al ‘03)

Hierarchical Communication

Hierarchical Data Fusion

Estimation in Action

FIGURE Sensor network protocol stack. (Reprinted from Akyildiz, I.F. et al., Computer Networks,Vol. 38, 393–422, 2002. With permission.)

Sensor Nodes:sense target events, gather sensor readings, manipulate informations, send them to gateway via radio link

Base station/sink: communicate with sensor nodes and user/operator, (database-stores the data)

Operator/user: task manager, send query

Task Management Plane

Mobility Management Plane

Power Management Plane

Application Layer: middleware, OSNetwork Layer: Routing

Application Layer

Transport Layer

Network Layer

Data Link Layer

Physical Layer

State of the art routing protocols are distributed and reactive : the systems start looking for a route only when they have application data to transmit

We study here Ad hoc On demand Distance Vector (AODV) and Dynamic Source Routing (DSR) for the sensor network

Route DiscoveryA node sends a Route Request message to all of its neighbours.Any node receiving such a request, either answers to it or rebroadcasts it.The procedure finishes either when the request sender has received theroute information, or when the request times out. With AODV, each node remembers the next hop information associated with

the destination. The route knowledge itself is distributed in the network.

With DSR, the complete route is sent to the route requester. Message transmission

With AODV, the message is sent to the next hop as recorded in the routing table, and this procedure is repeated at each hop.

With DSR, the message is sent with its complete route as header.

Rumor Routing

"Rumor Routing Algorithm for Sensor Network" by Braginsky and Estrin

How to make information available in a sensor network

Assumption: sense particular eventt when requested, don't know the existence or the location of the event

An event sends out agents which travel the network from node to node on a random path.Each visit leaves information about the event in the node's database. After a predefined TTL the agent stops

A requester also sends out an agent. After some time it will hopefully come across the path of the information agent by checking the node's databases. It can then travel the backward references the first agents left in the nodes to reach the event.

Critical review+ Only a small number of nodes have to adopt the same information

+ Only a small number of nodes have to process the request When or whether requested information can be delivered is a random process.- The failure of nodes can interrupt the path to the event (depending on how broad it is).- The actual behavior of a node is very different from what is shown in the former slides

Sensing: sensor --a transducer that converts a physical, chemical, or biological parameter into an electrical signal

Processing: microprocessor(CPU)

data storage(Mem)AD converter

Communicating: data transceiver(Radio),

Energy source: battery

68HC11

Node

Specific

OS Modules

Middleware

Middleware

Sensor

Driver

Node

Specific

OS Modules

Hardware Sensor

Middleware

ARMTemperature

Sensor

Sensor

Driver

Node

Specific OS

Modules

68HC11Pressure

Sensor

Node

Specific

OS Modules

Sensor

Driver

Middleware

Sensor Node

Model

• 68HC11 µC

• No Sensor

• ARM Microcontroller

• Temperature Sensor

• 68HC11 Microcontroller

• Pressure Sensor

Picoradio

(UCB)

WINS

(UCLA)Smart

Dust

(UCB)

Sensor,

Actuator

Battery

Processor HF

Characteristics of Sensor Nodes Limited capacity of Battery (Lifetime: day - 10 years) Processing capabilities (10MHz) Transmission range (5 - 20 meters)

Data rates: Bit/s - KB/s Transmission methods: 802.11 (WiFi) Bluetooth – short distance, other applications ZigBee – for sensor network

Price: some cents

Storage

persistent storage for data streams

Integrity Service/

Access Control

Query Manager

Storage

Sensor Manager

Query Manager

manages active queries

query processing

delivery of events and query results to registered, local or remote consumers

Integrity Service/

Access Control

Query Manager

Storage

Sensor Manager

Integrity Service/

Access Control

Query Manager

Storage

Sensor Manager

Top layer: access control and integrity service

OS examples: TinyOS: when an event

occurs, it calls the appropriate event handler to handle the event.

Others: Contiki, MANTIS, and SOS.

Create Hardware-optimized software components (driver, operating system )

Create hardware- independent software components (middleware, services)

Combining of predefined components Source code generation Removing unused components Optimizaion of interface Optimizaion to node's hardware

Distribution of nodes in different environments

Monitoring the execution Creation of logfiles

Evaluation of logfiles

Components

Design & Edit

Complie/Link

Distribute

Execute/Administrate

Evaluation

Resource Hardware

driven

Monitoring

Optimization

www.themegallery.com

2:Securityapplication

4:Medical Application

1: Militaryapplications

3:Environmental application

5:Commercial application

Location of combatants, vehicles and weapons

on the battlefield

It may be used to monitor patients from a distance

•Report a possible outbreak of fire•Detect dry areas

Detect movements of the earth to predict earthquake

Facilitate stock management

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17/24

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Based on the IEEE 802.15.4 Standard

Popular for WSN devices.

ZigBee adds:

Network topologies

Interoperability with other wireless products

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TinyOS is a free and open source operating system.

TinyOS is an embedded operating system written in the

nesC.

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Given:

Field A

N sensors

How well can the field be observed ?

Closest Sensor (minimum distance) only

Worst Case Coverage: Maximal Breach Path

Best Case Coverage: Maximal Support Path

Multiple Sensors: speed and path considered

Minimal Exposure Path

Applications of Wireless Sensor Networking:

In the present era there are lot of technologies which are used for monitoring are completely based on the wireless sensor networking. Some of important applications are environmental monitoring, traffic control application, weather checking, regularity checking of temperature etc. Wireless sensor networks can also be used for detecting the presence of vehicles such as motor cycles up to trains. These are some important wireless sensor networking based technologies which help us in our daily life. Some of there daily life applications are: used in agriculture, water level monitoring, green house monitoring, landfill monitoring etc.

In studying the performance or a wireless sensor network, you must take into consideration the deployment scenario which includes; topology, radio ranges, trajectory of targets and event traffic, and trajectories of user nodes and query traffic. All of these affect design trade-offs, and therefore any algorithm or protocol chosen should be evaluated under diverse deployment scenarios.

© 2003 –2004 by Yu Hen Hu 45

Sensor network is a new application area for computer vision, graphics and image processing

It requires multi-modality, multimedia processing under the constraint of minimizing communication and energy consumption.

Sensor Network can be used in many applications, such as Military, Environmental and Health…etc.

Its characteristics are tiny node, low power, limited resources, dynamic network topology and various scales of network deployment.

Middleware is used to connect the network hardware, operating systems, network stacks, and applications in different approaches.

For examples, Virtual Machine, Mobile Agent, Database and Message Oriented.

Security in Sensor Networks. Public/Private Key

▪ Key establishment beyond sensor network capabilities.

Shared Key▪ Simple solution, but single node may reveal the secret key.▪ Scalability? → each node stores n-1 keys (n(n-1) keys need to be

established)

Solution? Privacy Aspects in Sensor Networks. Sensor technology may be used for illegal surveillance. Providing awareness of the presence of sensor nodes? Solution?

FIGURE Sensor signal processing flow.

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ISI team experimented with three iPAQ-based video sender nodes and collected video baseline of several vehicles. RTP packet dumps and VHS video tape.

VT team supported BBN integrated experiment with Sensoria 2.0 nodes.

UCLA ran developmental experiments on sensor field coverage algorithms (under Sensorware project).

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