CISB422-Emerging Technologies-Sensor Networksx - MetaLab

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21 Νοε 2013 (πριν από 3 χρόνια και 7 μήνες)

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CISB422

Sensor Networks


Definition:


Wiki: consists of spatially distributed
autonomous

sensors

to
monitor

physical or environmental
conditions, such as
temperature
,
sound
,
pressure
,
etc. and to cooperatively pass their data through
the network to a main location


Key to gathering information needed by
smart environments



Sensor


An object which performs sensing
task

Sensing


Technique to gather information about
physical object or processes including
the occurrences of events


Sensor


A device that detects a change in a physical
stimulus and turns it into a signal which can be
measured or recorded


Transducer


A device that transfers power from one system to
another in the same of different form



Which sensor for which application?


Stimulus, specifications, physical phenomenon,
conversion mechanism, material and application


Stimulus


Acoustic, electric, magnetic, optical, thermal, mechanical


Physical property to be monitored


Temperature, chemical, light, humidity, position, motion


Active


Require external power supply


Passive


Detect energy and derive power from the energy
input

Physical

Property

Sensor

Temperature

Thermocouple

Silicon

Resistance temperature detector (RTD)

Thermistor

Force/Pressure

Strain Gauge

Piezoelectric

Acceleration

Accelerometer

Flow

Transducer

Transmitter

Position

Linear Variable Differential Transformers (LVDT)

Light Intensity

Photodiode


Networks of nodes that sense and potentially
also control their environment. They
communicate the information through
wireless links “enabling interaction between
people or computers and the surrounding
environment”


Verdone

et all, 2008


A collection of small randomly dispersed
devices that provide 3 main functions:
-


Ability to monitor physical and environmental
conditions (real time)


Ability to operate devices that control the
conditions


Ability to provide efficient, reliable
communications via wireless network


Defense Advanced Research Projects Agency
(DARPA)


1978: Distributed Sensor Nets Workshop


Early 1980s:


Distributed Sensor Networks (DSN)


Sensor Information Technology (
SensIT
) program



Rockwell Science Center, UCLA


1996: Low Power Wireless Integrated
Microsensor

(LWIM)


UC Berkeley


Smart Dust project (motes)


Berkeley Wireless Research Center


Low
-
power sensor device


MIT


μAMPS

project
-
low power hardware and software
components for sensor nodes


Network Topology


Communication Protocols and Routing


Sensor Node Architecture


Point to Point



Star



Mesh



Extended Star


Routing protocols depends on:


Power and resource limitations of the network nodes


Time
-
varying quality of the wireless channel


Possibility for packet loss and delay


First class:


Flat network architecture: all nodes are peers


Second class


Structured: nodes are organized in clusters based on residual
energy


Third class


Data
-
centric approach to disseminate interest: attribute based
naming


Fourth class


Uses location to address a sensor node


Low Energy Adaptive Clustering Hierarchy
(LEACH)


Clustering
-
based protocol


Utilizes randomized rotation of the cluster
-
heads
to evenly distribute the energy load among sensor
nodes in the network


Assume base station is fixed and far from sensors,
all nodes are homogenous and energy
-
constrained



Power Efficient Gathering in Sensor
Information System (PEGASIS)


Chain
-
based power efficient protocols based on
LEACH


Near optimal


All nodes have location information about all other
nodes and each has the capability of transmitting data
to base station directly


Sensor nodes are immobile


Threshold Sensitive Energy Efficient Sensor
Network (TEEN)


Cluster based routing protocol


Network is composed of a base station and sensor
nodes with the same initial energy


Base station has a constant power supply and can
transmit with high power to all the nodes directly


Flooding and Gossiping


Simple, less maintenance


Each node which receives data sends the packet
to its neighbors


IEEE 1451


WirelessHart


ZigBee

/ 802.15.4


ZigBee

IP


6LoWPAN


Energy


Self
-
Management


Wireless Networking


Decentralized Management


Design Constraints


Security


Others


Ad Hoc Deployment


No predetermined and engineered locations of individual sensor
nodes


Unattended Operation


Operate without human intervention: configuration, adaptation,
maintenance, repair must be performed autonomously


Self organization: network’s ability to adapt configuration parameters
based on system and environmental state


Self optimization: device’s ability to monitor and optimize the use of
its own resources


Self protection: device’s ability to recognize and protect itself from
intrusions and attacks


Self healing: device’s ability to discover, identify, react to network
disruptions



Attenuation: RF signal fades


Larger distance between base station and sensor
node requires more transmission power


Must support multi
-
hop communications
and
routing


Due to large scale and energy constraint


Results are not optimal, but more energy
efficient


Sensitive information


Exposed to malicious intrusions and attacks


Wireless:
-
eavesdrop on sensor transmission


Denial of service
attack


Use of
jamming attack
: high powered wireless
signals are used to prevent successful sensor
communications

Traditional Networks

Wireless

Sensor Networks

General purpose design; serving many
applications

Single purpose design, serving one
specific application

Typical primary design concerns

are
network performance and latencies;
energy is not a primary concern

Energy is the

main constraint in the
design of all node and network
components

Networks are

designed and engineered
according to plans

Deployment,

network structure, and
resource use are often ad hoc

Devices and networks operate

in
controlled and mild environments

Sensor

networks often operate in
environments with harsh conditions

Maintenance and repair are common

and
networks are easy to access

Physical access to sensor nodes is often

difficult and even impossible

Component failure is

addressed through
maintenance and repair

Component failure is expected and
addressed in the

design of the network

Obtaining global network knowledge

is
typically feasible and centralized
management is possible

Most decisions are made localized

without the support of a central manager


Applications:


Air, soil and water monitoring


Condition based maintenance


Habitat monitoring


Seismic detection


Military surveillance


Inventory tracking


Smart spaces


Structural Health Monitoring


Traffic Control


Health Care


Pipeline monitoring


Precision Agriculture


Active Volcano


Underground Mining


Smart City



Heating, ventilation, and air conditioning
systems (HVAC)


Lightning


Shading


Air quality and window control


Systems switching off devices


Metering (covered in the section on smart grids)


Standard household applications (
e.g.
televisions, washing machines)


Security and safety (access control).



Consumes 30% less energy than traditional
skycrappers


Has a curtain wall
-
serves as sunscreen and
changes color during the day


Shading system
-
tracks the sun position and
relies on sensor network to automatically
actuate the raising and lowering of the
shades


HVAC system is equipped with temperature
sensors; rely on free air cooling



Temperature sensors and heat detectors


Light level detectors


Movement and occupancy sensors


Smoke and gas detectors


Status sensors (
e.g. air quality, open windows)


Glass break sensors



Plant/crop monitoring


Soil monitoring


Climate monitoring


Insect
-
disease
-
weed monitoring


Example:


Low Frequency Array (LOFAR) Agro Project


Measured micro climate in a potato field to provide
information on how to fight fungal disease and
phytophra