Wireless Sensor Networks - Introduction

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Wireless Sensor Networks - Introduction

• Sensors in WSN
• Sensing node
• Wireless Sensor Netwworks
• Communication in WSN
• Challenges and Constraints
• Selected applications of WSN

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1. Sensors in WSN
Data acquisition and actuation

• Signal conditioning
• amplification (or attenuation) to change
• the signal magnitude
• filters to the signal to remove unwanted noise
  within certain frequency ranges (e.g., highpass
  filters can be used to remove 50 or 60 Hz noise
  picked up by surrounding power lines)

• An actuator can be
• a valve controlling the flow of hot water,
• a motor that opens or closes a door or window,
• a pump that controls the amount of fuel
  injected into an engine.

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2. Sensing node

• The components of a sensing node include
• sensing and actuation unit
• processing unit
• communication unit
• power unit
• other application-dependent units

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The term sensor node is the most general. The
terms Smart Dust, mote and COTS (commercial
off-the-shelf) mote are used somewhat
interchangeably in the industry.
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3. Wireless sensor networks
A wireless sensor has not only a sensing
component, but also on-board processing,
communication, and storage capabilities. With
these enhancements, a sensor node is often not
only responsible for data collection, but also
for in-network analysis, correlation, and fusion
of its own sensor data and data from other sensor
nodes. When many sensors cooperatively monitor
large physical environments, they form a wireless
sensor network (WSN).
Sensor nodes communicate not only with each other
but also with a base station (BS) using their
wireless radios, allowing them to disseminate
their sensor data to remote processing,
visualization, analysis, and storage systems.
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4. Communication in WSN

• The well-known IEEE 802.11 family of standards
  was introduced in 1997 and is the most common
  wireless networking technology for mobile
  systems.
• It uses different frequency bands, for example,
• 2.4-GHz band is used by IEEE 802.11b and IEEE
  802.11g,
• 5 GHz for IEEE 802.11a.
• Data rates provided by IEEE 802.11 are typically
  much higher than needed
• This has led to the development of a variety of
  protocols that better satisfy the networks need
  for low power consumption and low data rates.
• For example,the IEEE 802.15.4 protocol has been
  designed for short-range communications in
  low-power sensor networks and is supported by
  most academic and commercial sensor nodes.

Single-hop versus multi-hop communication in
sensor networks. When the transmission ranges of
the radios of all sensor nodes are large enough
and the sensors can transmit their data directly
to the base station, they can form a star
topology. In mesh topology, sensor nodes must
not only capture and disseminate their own data,
but also serve as relays for other sensor nodes,
that is, they must collaborate to propagate
sensor data towards the base station.
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Standards for Transport Protocols
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5. Challenges and Constraints
5.1. Energy
The most often met constraint is that sensor
nodes operate with limited energy budgets.
Typically, they are powered through batteries,
which must be either replaced or recharged (e.g.,
using solar power). For some nodes, neither
option is appropriate, that is, they will simply
be discarded once their energy source is
depleted. For nonrechargeable batteries, a
sensor node should be able to operate until
either its mission time has passed or the battery
can be replaced (monitoring glacial movements may
need sensors that can operate for several years
while a sensor in a battlefield scenario may only
be needed for a few hours or days). The energy
consumption of CMOS-based processors is primarily
due to switching energy and leakage
energy ECPU Eswitch Eleakage CtotalV
dd2 Vdd Ileak t where Ctotal is the total
capacitance switched by the computation, Vdd is
the supply voltage, Ileak is the leakage current,
and t is the duration of the computation. Switchi
ng energy still dominates the energy consumption
of processors. It is expected that in future
processor designs, the leakage energy will be
responsible for more than half the energy
consumption.
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5.2. Self-Management
Sensor nodes must be self-managing in that they
configure themselves, operate and collaborate
with other nodes, and adapt to failures, changes
in the environment, and changes in the
environmental stimuli without human intervention.
Ad Hoc Deployment Sensors serving the assessment
of battlefield or disaster areas could be thrown
from airplanes over the areas of interest, but
many sensor nodes may not survive such a drop and
may never be able to begin their sensing
activities. The surviving nodes must autonomously
perform a variety of setup and configuration
steps, including the establishment of
communications with neighboring sensor nodes,
determining their positions, and the initiation
of their sensing responsibilities.
Unattended Operation Many sensor networks, once
deployed, must operate without human
intervention, that is, configuration, adaptation,
maintenance, and repair must be performed in an
autonomous fashion. A self-managing device will
monitor its surroundings, adapt to changes in the
environment, and cooperate with neighboring
devices to form topologies or agree on sensing,
processing, and communication strategies.
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5.3. Wireless Networking
Attenuation limits the range of radio signals,
that is, a radio frequency (RF) signal fades
(i.e., decreases in power) while it propagates
through a medium and while it passes through
obstacles. The relationship between the received
power PR and transmitted power PT of an RF signal
can be expressed using the inverse-square
law An increasing distance between a sensor
node and a base station rapidly increases the
required transmission power. Therefore, it is
more energy-efficient to split a large distance
into several shorter distances, leading to the
challenge of supporting multi-hop communications
and routing. Due to this challenge networks
employ duty cycles to preserve energy, that is,
many sensor nodes use a power conservation policy
where radios are switched off when they are not
in use. As a consequence, during these
down-times, the sensor node cannot
receive messages from its neighbors nor can it
serve as a relay for other sensors. Therefore,
some networks rely on wakeup on demand strategies
to ensure that nodes can be woken up whenever
needed. Usually this involves devices with two
radios, a low-power radio used to receive wakeup
calls and a high-power radio that is activated in
response to a wakeup call. Another strategy is
adaptive duty cycling, when not all nodes are
allowed to sleep at the same time. Instead, a
subset of the nodes in a network remain active to
form a network backbone.
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5.4. Decentralized Management
Centralized algorithms (e.g., executed at the
base station) to implement network management
solutions such as topology management or routing
may be ifeasible due to yhe large scale and the
energy constraints. Instead, sensor nodes must
collaborate with their neighbors to make
localized decisions, that is, without global
knowledge. As a consequence, the results of
these decentralized (or distributed ) algorithms
will not be optimal, but they may be more
energy-efficient than centralized solutions.
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5.5. Design Constraints
While the capabilities of traditional computing
systems continue to increase rapidly, the primary
goal of wireless sensor design is to create
smaller, cheaper, and more efficient
devices. Due to this, typical sensor nodes have
the processing speeds and storage capacities of
computer systems from several decades ago. These
constraints and requirements also impact the
software design at various levels, for example,
operating systems must have small memory
footprints and must be efficient in their
resource management tasks. However, the lack of
advanced hardware features (e.g., support for
parallel executions) facilitates the design of
small and efficient operating systems. A
sensors hardware constraints also affect the
design of many protocols and algorithms executed
in a WSN. While in-network processing can be
employed to eliminate redundant information, some
sensor fusion and aggregation algorithms may
require more computational power and storage
capacities than can be provided by low-cost
sensor nodes. Therefore, many software
architectures and solutions (operating system,
middleware, network protocols) must be designed
to operate efficiently on very resource-constraine
d hardware.
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5.6. Security
The remote and unattended operation of sensor
nodes increases their exposure to malicious
intrusions and attacks. One of the most
challenging security threats is a
denial-of-service attack, whose goal is to
disrupt the correct operation of a sensor
network. This can be achieved using a variety of
attacks, including a jamming attack , where
high-powered wireless signals are used to prevent
successful sensor communications. While there
are numerous techniques and solutions for
distributed systems that prevent attacks, many of
these incur significant computational,
communication, and storage requirements, which
often cannot be satisfied by resource-constrained
sensor nodes. As a consequence, sensor networks
require new solutions for key establishment and
distribution, node authentication, and secrecy.
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5.7. Other Challenges
Comparison of traditional networks and wireless
sensor networks
While traditional computer networks are based on
established standards, many protocols
and mechanisms in wireless sensor networks are
proprietary solutions, while standards-based
solutions emerge only slowly. Standards are
important for interoperability and facilitate the
design and deployment of WSN applications
therefore, a key challenge in WSN design remains
the standardization of promising solutions and
the harmonization of competing standards.
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6. Selected applications of WSN
Home control
Home control applications provide control,
conservation, convenience and safety. Body-worn
medical sensors (e.g. heartbeat sensors) are also
emerging.
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Building Automation

• Building automation provide control,
  conservation, flexibility and safety as follows
• management of lighting, heating,
• cooling and safety
• control of systems to improve conservation
• optimized HVAC management
• rapid reconfiguring the lighting system to
  create adaptable workspaces
• enable to network and integrate data from
  multiple access control points.

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Industrial Automation

• Industrial automation applications provide
• process control systems reliability
• reduce energy costs
• identification of poorly performing equipment
  and inefficient operations
• provide detailed data to improve preventive
  maintenance
• help deploy monitoring networks to enhance
  employee and public safety.

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Medical Applications
PDA displaying real-time vital signs of multiple
patients.
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Security Applications

• Military sensor networks detect
• information about enemy movements,
• explosions etc.
• law enforcement and national security
  applications (figure)
• sensor networks to detect chemical, biological,
  radiological and explosive attacks and material
• environmental changes in forests, oceans and so
  on
• monitoring of vehicle traffic on highways or in
  congested parts of a city
• parking lot occupation sensor networks
• borders monitoring with sensors ans sattelite
  uplinks.

Real time monitoring and sensor interrogation
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Highway Monitoring
Traffic in US is growing at three times the rate
of population growth. Traffic Pulse Technology
(US) is an example of a system using stationary
WNs, which collects data through sensor network,
processes and stores the data in a data
center. Temperature, pollution levels are
collected in real-time. Digital sensor network
gathers lane-by-lane data on travel speeds, lane
occupancy and vehicle counts. The data are
transmitted to the data center for reformatting
(every 60 seconds).
Typical highway traffic-sensing installation
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Civil Engineering Applications
Sensor technology is aplicable for buildings,
bridges and other structures. The picture shows
a prototype WSN developed at the University of
California, Berkeley, and deployed at the Golden
Gate Bridge in San Francisco. The bridge has a
center span that sustains a maximum transverse
deflection (due to wind or earthquake) of 27.7 ft
and maximum upward and downward deflections of
5.8 ft and 10.8 ft, respectively. The towers are
500 ft high above the roadway and 746 ft high
above the water. The tops of the towers can have
transverse deflections of up to 12.5 in. and
toward the shore longitudinal deflections of 22
in. Sixty-four wireless sensor nodes were
deployed on this bridge to establish a structural
health monitoring network. The nodes were
distributed over the main span and the tower,
collecting ambient vibrations synchronously, at a
rate of 1 kHz, with less than 10 µs jitter and
with an accuracy of 30 µG. Data is collected
reliably over a 46-hop network.
The deployment scenario of nodes on the Golden
Gate Bridge a) the nodes are deployed on both
sides of the span. b) a
two-dimensional view of the placement of nodes on
the bridge.