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Chapter -1
INTRODUCTION AND OVERVIEW
OF WIRELESS SENSOR NETWORKS
BY
USHA PADMA
Assistant Professor
Telecommunication Department
R V College of Engineering
INTRODUCTION
A sensor network is an infrastructure comprised of
sensing (measuring), computing, and communication
elements that gives an administrator the ability to
instrument, observe, and react to events and phenomena
in a specified environment.
There are four basic components in a sensor network:
(1) an assembly of distributed or localized sensors;
(2) an interconnecting network (usually, but not always,
wireless-based);
(3) a central point of information clustering; and
(4) a set of computing resources at the central point (or
beyond) to handle data correlation, event trending, status
querying, and data mining.
Background of Sensor Network Technology
īƒ¨ The technology for sensing and control includes
electric and magnetic field sensors;radio-wave
frequency sensors; optical-, electrooptic-, and
infrared sensors;radars; lasers; location/navigation
sensors; seismic and pressure-wave sensors;
environmental parameter sensors (e.g., wind,
humidity, heat); and biochemical national security–
oriented sensors.
īƒ¨ Sensor devices, or wireless nodes (WNs), are also
(sometimes) called motes.
īƒ¨ A stated commercial goal is to develop complete
microelectromechanical systems (MEMSs)–based
sensor systems at a volume of 1 mm3
Background of Sensor Network Technology
īƒ¨ Within the sensor field, WSNs employ contention-oriented random-
access channel sharing and transmission techniques that are now
incorporated in the IEEE 802 family of standards.
īƒ¨ AWSN consists of densely distributed nodes that support sensing,
signal processing, embedded computing, and connectivity; sensors
are logically linked by self organizing means (sensors that are
deployed in short-hop point-to-point master–slave pair
arrangements are also of interest).
īƒ¨ WSNs have unique characteristics, such as power constraints and
limited battery life for the WNs, redundant data acquisition, low
duty cycle, and, many-to-one flows.
Background of Sensor Network Technology
īƒ¨ Sensors span several orders of magnitude in
physical size; they (or, at least some of their
components) range from nanoscopic-scale devices
to mesoscopic-scale devices at one end, and from
microscopic-scale devices to macroscopic-scale
devices at the other end.
īƒ¨ Embedded network sensing refers to the synergistic
incorporation of microsensors in structures or
environments; embedded sensing enables spatially
and temporally dense monitoring of the system
under consideration (e.g., an environment, a
building, a battlefield).
Background of Sensor Network Technology
īƒ¨ Sensors facilitate the instrumenting and controlling
of factories, offices, homes, vehicles, cities, and the
ambiance, especially as commercial off-the-shelf
technology becomes available.
īƒ¨ A current research and development (R&D)
challenge is to develop low-power communication
with low-cost on-node processing and selforganizing
connectivity/protocols; another critical challenge is the
need for extended temporal operation of the sensing
node despite a (typically) limited power supply
(and/or battery life).
Background of Sensor Network Technology
īƒ¨ Power efficiency in WSNs is generally accomplished
in three ways:
1. Low-duty-cycle operation.
2. Local/in-network processing to reduce data volume
(and hence transmission time).
3. Multihop networking reduces the requirement for
long-range transmission since signal path loss is an
inverse exponent with range or distance. Each node
in the sensor network can act as a repeater, thereby
reducing the link range coverage required and, in
turn, the transmission power.
Background of Sensor Network Technology
Sensor networks and systems are taxomised into two
categories:
īƒ¨ Category 1 WSNs (C1WSNs): almost invariably mesh-based
systems with multihop radio connectivity among or between WNs,
utilizing dynamic routing in both the wireless and wireline portions
of the network. Military theater systems typically belong to this
category.
īƒ¨ Category 2 WSNs (C2WSNs): point-to-point or multipoint-to-
point (starbased) systems generally with single-hop radio
connectivity to WNs, utilizing static routing over the wireless
network; typically, there will be only one route from the WNs to the
companion terrestrial or wireline forwarding node (WNs are
pendent nodes). Residential control systems typically belong to this
category.
Standardization of WSN
â€ĸWithin building, Wi-Fi (IEEE 802.11b) was ruled out.
â€ĸInfrared systems were not suitable.
â€ĸ Bluetooth was too complex and expensive.
â€ĸ IEEE 802.15.4 with ZigBee.
â€ĸZigBee comprises the software layers above IEEE 802.15.4.
â€ĸ IEEE 802.15.4 operates in 2.4 GHz ISM radio band.
â€ĸ Data rate upto 250 kbps ranging from 30 to 200ft.
Background of Sensor Network Technology
īƒ¨ There is also considerable research in the area of
mobile ad hoc networks (MANETs). WSNs are
similar to MANETs in some ways; for example, both
involve multihop communications. The applications
and technical requirements for the two systems are
significantly different in several respects
DAWN Lab / UMBC 10
Background of Sensor Network Technology
īƒ¨ The typical mode of communication in WSN is from multiple data
sources to a data recipient or sink (somewhat like a reverse
multicast) rather than communication between a pair of nodes. In
other words, sensor nodes use primarily multicast or broadcast
communication, whereas most MANETs are based on point-to-
point communications.
īƒ¨ In most scenarios (applications) the sensors themselves are not
mobile (although the sensed phenomena may be); this implies that
the dynamics in the two types of networks are different.
īƒ¨ Because the data being collected by multiple sensors are based on
common phenomena, there is potentially a degree of redundancy in
the data being communicated by the various sources in WSNs; this
is not generally the case in MANETs.
Background of Sensor Network Technology
īƒ¨ Because the data being collected by multiple sensors are based on
common phenomena, there is potentially some dependency on
traffic event generation in WSNs, such that some typical random-
access protocol models may be inadequate at the queueing-analysis
level; this is generally not the case in MANETs.
īƒ¨ A critical resource constraint in WSNs is energy; this is not always
the case in MANETs, where the communicating devices handled by
human users can be replaced or recharged relatively often. The
scale of WSNs (especially, C1WSNs) and the necessity for
unattended operation for periods reaching weeks or months implies
that energy resources have to be managed very judiciously. This, in
turn, precludes high-data-rate transmission.
īƒ¨ The number of sensor nodes in a sensor network can be several
orders of magnitude higher than the nodes in a MANET.
Applications of Sensor Networks
īƒ¨ Military applications.
īƒ¨ Environmental applications.
īƒ¨ Health applications.
īƒ¨ Home applications.
īƒ¨ Commercial applications.
ī‚§ Smart spaces
Basic Sensor Network Architectural Elements
īƒ¨ These elements and design principles need to be placed in the
context of the C1WSN sensor network environment, which is
characterized by many (sometimes all) of the following factors:
īƒ¨ Large sensor population
īƒ¨ Large streams of data,
īƒ¨ Incomplete/uncertain data,
īƒ¨ High potential node failure; high
īƒ¨ Potential link failure (interference),
īƒ¨ Electrical power limitations,
īƒ¨ Processing power Limitations,
īƒ¨ Multihop topology,
īƒ¨ Lack of global knowledge about the network, and
īƒ¨ Limited administrative support for the network.
Sensor Types and Technology
A sensor network is composed of a large number of
sensor nodes that are densely deployed.
īƒ¨ Sensor nodes may be deployed in an open space; on a
battlefield in front of, or beyond, enemy lines; in the interior of
industrial machinery; at the bottom of a body of water; in a
biologically and/or chemically contaminated field; in a
commercial building; in a home; or in or on a human body.
īƒ¨ Sensor nodes are scattered in a special domain called a
sensor field.
īƒ¨ Each of the distributed sensor nodes typically has the
capability to collect data, analyze them, and route them to a
(designated) sink point.
Typical sensor network arrangement.
īƒ¨ Embedded sensor networks are predicated on three supporting
components: embedding, networking, and sensing.
īƒ¨ Embedding implies the incorporation of numerous distributed
devices to monitor the physical world and interact with it; the
devices are untethered nodes of small form factors that are
equipped with a control and communication subsystem. Spatially-
and temporally-dense arrangements are common.
īƒ¨ Networking implies the concept of physical and logical
connectivity. Logical connectivity has the goal of supporting
coordination and other high-level tasks; physical connectivity is
typically supported over a wireless radio link.
īƒ¨ Sensing implies the presence of these capabilities in a tightly
coupled environment, typically for the measurement of physical-
world parameters.
Features of sensor networks
īƒ¨ Sensor nodes are densely deployed.
īƒ¨ Sensor nodes are prone to failures.
īƒ¨ The topology of a sensor network changes very
frequently.
īƒ¨ Sensor nodes are limited in power, computational
capacities, and memory.
īƒ¨ Sensor nodes may not have global identification because
of the large amount of overhead and the large number of
sensors.
Typical Sensing node
īƒ¨ Sensor networks require sensing systems that are long-
lived and environmentally resilient. Unattended,
untethrered, self-powered low-duty-cycle systems are
typical.
īƒ¨ Sensors are either passive or active devices.
īƒ¨ Passive sensors in element form include seismic-,
acoustic-, strain-, humidity-, and temperature-measuring
devices. They tend to be low-energy devices.
īƒ¨ Active sensors include radar and sonar; these tend to be
high-energy systems. The trend is toward VLSI (very
large scale integration), integrated optoelectronics, and
nanotechnology;
īƒ¨ In addition to (embedded) sensing there is a desire
to build, deploy, and manage unattended or
untethered embedded control and actuation
systems, sometimes called control networks.
īƒ¨ Such a control system acts on the environment
either in a self-autonomous manner or under the
telemetry of a remote or centralized node.
īƒ¨ Key applications require more than just sensing:
They need control and actuation.
Software (Operating Systems and Middleware)
īƒ¨ To support the node operation, it is important to have open-
source operating systems designed specifically for WSNs.
īƒ¨ Such operating systems typically utilize a component-based
architecture that enables rapid implementation and
innovation while minimizing code size as required by the
memory constraints endemic in sensor networks.
īƒ¨ Tiny OS is one such example of a de facto standard, but not
the only one.
īƒ¨ Tiny OS’s component library includes network protocols,
distributed services, sensor drivers, and data acquisition
tools.
Standards for Transport Protocols
īƒ¨ The goal of WSN engineers is to develop a cost-
effective standards-based wireless networking
solution that supports low-to medium data rates, has
low power consumption, and guarantees security
and reliability.
Generic Protocol Stack for Sensor networks
īƒ¨ Combine power and
routing awareness
īƒ¨ Integrates data with
networking protocols
īƒ¨ Communicates power
efficiently through the
wireless medium
īƒ¨ Promotes cooperative
efforts among sensor
nodes.
Possible Lower –Layer WSN Protocols
Physical layer:
Communication channel, sensing , actuation and
signal processing.
Address the needs of simple but robust modulation,
transmission, and receiving techniques.
īƒ¨ frequency selection.
īƒ¨ carrier frequency generation.
īƒ¨ signal detection and propagation.
īƒ¨ signal modulation and data encryption.
Data link layer
:
The data link layer is responsible for the multiplexing
of data stream, data frame detection, the medium
access and error control.
īƒ¨ Medium Access Control
īƒ¨ Power Saving Modes of Operation
īƒ¨ Error Control
Network layer:
īƒ¨ Power efficiency is always an important
consideration.
īƒ¨ Sensor networks are mostly data centric.
īƒ¨ Data aggregation is useful only when it does not
hinder the collaborative effort of the sensor nodes.
īƒ¨ An ideal sensor network has attribute-based
addressing and location awareness.
īƒ¨ Adaptive topology management and topological
routing.
Transport layer:
īƒ¨ This layer is especially needed when the system is
planned to be accessed through Internet or other
external networks.
īƒ¨ TCP/UDP type protocols meet most requirements
(not based on global addressing).
īƒ¨ Data dissemination and accumulation, caching and
storage.
Upper layer:
Management protocol makes the hardware and
software of the lower layers transparent to the
sensor network management applications.
īƒ¨ Sensor management protocol (SMP)
īƒ¨ Task assignment and data advertisement protocol
(TADAP)
īƒ¨ Sensor query and data dissemination protocol
(SQDDP)
īƒ¨ Application processing, data aggregation, external
querying query processing, and external database.
Routing and Data Dissemination
Routing protocols for WSNs generally fall into three
groups:
īļ Data-centric : SPIN, GBR, CADR, Directed diffusion
Rumor routing, etc.
īļ Hierarchical : LEACH, TEEN, APTEEN, PEGASIS,
etc.
īļ Location-based :MECN, SMECN, GAF and GEAR.
īļ QoS-oriented : SAR and SPEED.
31
32
Network Design Issues
īƒ¨ Issues relate to reliable transport (possibly including
encryption), bandwidth-and power limited
transmission, data-centric routing, in-network
processing, and self configuration.
īƒ¨ Design factors include operating environment and
hardware constraints such as transmission media,
radio-frequency integrated circuits, power
constraints, communications network interfaces; and
network architecture and protocols, including
network topology and fault tolerance, scalability,
self-organization, and mobility.
33
Brief Historical Survey of Sensor Networks
The history of sensor networks spans four phases:
īƒ˜ Phase 1: Cold-War Era Military Sensor Networks.
īƒ˜ Phase 2: Defense Advanced Research Projects
Agency Initiatives.
īƒ˜ Phase 3: Military Applications Developed or
Deployed in the 1980s and 1990s.
īƒ˜ Phase 4: Present-Day Sensor Network Research.
Applications of WSN
WSNs are collections of compact-size, relatively
inexpensive computational nodes that measure local
environmental conditions or other parameters and
forward such information to a central point for
appropriate processing. WSNs nodes (WNs) can sense the
environment, can communicate with neighboring nodes,
and can, in many cases, perform basic computations on
the data being collected. WSNs support a wide range of
useful applications.
EXAMPLES OF CATEGORY 1 WSN APPLICATIONS
Some examples of WSN applications are :
īƒŧ Military sensor networks to detect and gain as much
information as possible about enemy movements,
explosions, and other phenomena of interest.
īƒŧ Law enforcement and national security applications for
inimical agent tracking or nefarious substance
monitoring.
īƒŧ Sensor networks to detect and characterize chemical,
biological, radiological, nuclear, and explosive (CBRNE)
attacks and material.
īƒŧSensor networks to detect and monitor environmental
changes in plains, forests, oceans, and so on.
EXAMPLES OF CATEGORY 1 WSN APPLICATIONS
īƒŧ Wireless traffic sensor networks to monitor vehicle
traffic on highways or in congested parts of a city.
īƒŧ Wireless surveillance sensor networks for providing
security in shopping malls, parking garages, and other
facilities.
īƒŧWireless parking lot sensor networks to determine which
spots are occupied and which are free.
īƒŧBorders monitoring with sensors and satellite uplinks.
Sensor and Robots
Two technologies appear poised for a degree of
convergence: mobile robotics and wireless sensor
networks. The field of mobile robotics deals with
mechanical aspects (the wheels, motors, grasping arms,
or physical layout) as well as with the logic aspects. Two
questions of interest are :
īą Can a mobile robot act as a gateway into a wireless
sensor network?
īąCan sensor networks take advantage of a robot’s
mobility and intelligence?
To affect this convergence, inexpensive standards-based
hardware, open-source operating systems, and off-the-
shelf connectivity modules are required.
Intel fab environment with WSNs
Theme park WSN example
Reconfigurable Sensor Networks
Military applications require support for tactical and
surveillance arrangements that employ reconfigurable
sensor WNs that are capable of forming networks on the
fly, assembling themselves without central control, and
being deployed incrementally. Reconfigurable ‘‘smart’’
WNs are self-aware, self-configurable, and autonomous.
Self-organizing WSNs utilize mechanisms that allow newly
deployed WNs to establish connectivity (to build up a
network topology) spontaneously. Also, these networks
have mechanisms for managing WN mobility (if any), WN
reconfiguration, and WN failure.
Highway Monitoring
ī‚§Transportation (traffic flow) is a sector that is expected
to benefit from increased monitoring and surveillance.
ī‚§The system is installed along major highways; the digital
sensor network gathers lane-by-lane data on travel
speeds, lane occupancy, and vehicle counts. These basic
data elements make it possible to calculate average
speeds and travel times. The data are then transmitted to
the data center for reformatting. The network monitors
roadway conditions continuously on a 24/7 basis and
provides updates to the data center in real time. The
system collects key traffic information, including vehicle
speeds, counts (volume), and roadway density,
transmitting the data over a wireless network to a data
center every 60 seconds.
Highway Monitoring
Applications include the following:
1. Private traffic information providers in the United
States: The company’s realtime and archived data offer
valuable tools for a variety of commercial and
governmental applications.
2. Telematics: For mobile professionals and others, the
company’s traffic information complements in-vehicle
navigation devices, informing drivers not only how to
get from point A to point B but how long it will take to
get there, or even direct them to an alternative route.
Military Applications
Wireless distributed microsensor networks consist of a collection
of communicating nodes, where each node incorporates:
(1) One or more sensors for measuring the environment.
(2) Computing capability to process sensor data into ‘‘high-
value’’ information and to accomplish local control, and
(3) A radio to communicate information to and from neighboring
nodes and eventually to external users.
Civil and Environmental Engineering Applications
īƒ˜Sensors can be used for civil engineering applications.
īƒ˜The goal is to develop ‘‘smart structures’’ that are able
to self-diagnose potential problems and self-prioritize
requisite repairs(earthquake active zones).
īƒ˜The battery-powered matchbox-sized WNs operating on
Tiny OS are designed to sense a number of factors,
ranging from light and temperature (for energy-saving
applications) to dynamic response (for civil engineering
analysis).
Wildfire Instrumentation
īļCollecting real-time data from wildfires is important for
life safety considerations and allows predictive analysis of
evolving fire behavior.
īļOne way to collect such data is to deploy sensors in the
wildfire environment. FireBugs are small wireless sensors
(motes) based on TinyOS that self-organize into networks
for collecting real-time data in wildfire environments.
īļThe FireBug system combines state-of-the-art sensor
hardware running TinyOS with standard off-the-shelf
World Wide Web and database technology, allowing rapid
deployment of sensors and behavior monitoring.
Habitat Monitoring
īļThe goal was to develop a habitat-monitoring kit that
enables researchers worldwide to engage in nonintrusive
and nondisruptive monitoring of sensitive wildlife and
habitats.
īļAbout three dozen motes were deployed onthe island.
Each mote has a microcontroller, a low-power radio,
memory, and batteries.
īļSensor motes monitor the nesting habitat of Leach’s
storm petrel on the island and relay their readings into a
satellite link that allows researchers to download real-
time environmental data over the Internet.
īļFor habitat monitoring the planner needed sensors that
can take readings for temperature, humidity, barometric
pressure, and midrange infrared. Motes sample and relay
their sensor readings periodically to computer base
Nanoscopic Sensor Applications
ī‚§There is interest in the ‘‘labs on a chip’’ concept,
including new methodologies supported by
nanotechniques.
ī‚§In particular, a nanoscopic microscale confocal imaging
array (micro-CIA) is a device that merges MEMSs
(micro electromechanical systems), ultrasmall lasers,
lenses, and plumbing.
ī‚§These devices are fabricated by micromachining silicon
or polymers. Using this technology, one can detect
biowarfare pathogens and can use it as a diagnostic
tool in medicine.
Classification Factors
ANOTHER TAXONOMY OF WSN TECHNOLOGY
Three types of WSN system (technology) are:
1. Nonpropagating WSN systems
2. Deterministic routing WSN systems
a. Aggregating
b. Nonaggregating systems
3. Self-configurable and self-organizing WSN systems
a. Aggregating
b. Nonaggregating systems
EXAMPLES OF CATEGORY 2 WSN APPLICATIONS
C2WSN technology is being targeted for a gamut of
building automation, industrial, medical, residential
control, and monitoring applications. Many of these
applications are being contemplated in the context of the
IEEE 802.15.4 (ZigBee) standard solution. Examples of
applications include lighting controls; automatic meter
reading;wireless smoke and CO detectors; HVAC control;
heating control; home security; environmental controls;
blind, drapery, and shade controls; medical sensing and
monitoring; universal remote control to a set-top box
that includes home control, industrial automation, and
building automation.
īļ Home Control
īƒ¨ Zigbee is designed for low to very –low –duty cycle
static and dynamic environments with many active
nodes.
īƒ¨ Bluetooth is designed for high QOS, a variety of duty
cycles, and moderate data rates in networks with
limited active nodes.
īƒ¨ Battery arrangement based on two AA alkaline cells
or one Li-AA cell.
īƒ¨ Oscillator wake up the main processor.
īƒ¨ Security systems, 10 seconds to 15 minutes.
51
Battery longevity
52
Home Control
Home control applications provide control, conservation,
convenience, and safety, as follows:
īļSensing applications facilitate flexible management of
lighting, heating, and cooling systems from anywhere in
the home.
īļ Sensing applications automate control of multiple home
systems to improve conservation, convenience, and
safety.
īļ Sensing applications capture highly detailed electric,
water, and gas utility usage data.
īļSensing applications embed intelligence to optimize
consumption of natural resources.
Home Control continued
īļSensing applications enable the installation, upgrading,
and networking of a home control system without wires.
īļ Sensing applications enable one to configure and run
multiple systems from a single remote control.
īļ Sensing applications support the straightforward
installation of wireless sensors to monitor a wide variety
of conditions.
īļ Sensing applications facilitate the reception of
automatic notification upon detection of unusual
events.
Medical Applications
A number of hospitals and medical centers are exploring
applications of WSN technology to a range of medical
applications, including pre-hospital and in-hospital
emergency care, disaster response, and stroke patient
rehabilitation. WSNs have the potential to affect the
delivery and study of resuscitative care by allowing vital
signs to be collected and integrated automatically into the
patient care record and used for real-time triage,
correlation with hospital records, and long-term
observation. WSNs permit home monitoring for chronic
and elderly patients, facilitating long-term care and trend
analysis. WSNs also permit collection of long-term
medical information that populates databases of clinical
data; this enables longitudinal studies across populations
and allows physicians to study the effects of medical
intervention programs.
īƒ¨ Harvard University and others have developed
a small, wearable wireless pulse oximeter and two-
lead electrocardiogram (EKG).
īƒ¨ The data can be displayed in real time and
integrated into developing pre-hospital patient care
record.
īƒ¨ The sensor devices themselves can be programmed
to process the vital sign data.
56
īƒ¨ In collaboration with the Motion Analysis Laboratory
at the Spaulding Rehabilitation Hospital, Harvard
University has also developed a tiny wearable
device for monitoring the limb movements and
muscle activity of stroke patients during
rehabilitation exercise.
īƒ¨ These devices, consisting of three-axis
accelerometer, gyroscope, and electromyogram
sensors, allow researchers to capture a rich data set
of motion data for studying the effect of various
rehabilitation exercises on this patient population.
57
īƒ¨ In addition to the hardware platform, Harvard University developed
a scalable software infrastructure called CodeBlue, for wireless
medical devices.
īƒ¨ CodeBlue is designed to provide routing, naming, discovery, and
security for wireless medical sensors, PDAs, PCs, and other devices
that may be used to monitor and treat patients in a number of
medical settings.
īƒ¨ CodeBlue is designed to scale across a different network densities,
ranging from sparse clinic and hospital deployments to very dense
ad hoc deployments at a mass casualty site.
īƒ¨ Part of the CodeBlue system includes a system for tracking the
location of individual patient devices indoors and outdoors using
radio signal information.
58
Use of CodeBlue for emergency response
59
Basic Wireless Sensor Technology
Introduction
WSNs are characterized by the fact that they need to
operate in resource-constrained environments; in turn,
this fact imposes strict design guidelines and limitations
on the WNs.
sensor functionality and components, including the
sensing and actuation unit, processing unit,
communication unit, power unit, and other application-
dependent units are addressed.
SENSOR NODE TECHNOLOGY
At the design level a WSN sits at the confluence of
research in disciplines such as database query
processing, networking, algorithms, and distributed
systems. The basic functionality of a WN generally
depends on the application, but the following
requirements are typical :
ī‚§Determine the value of a parameter at a given location.
ī‚§Detect the occurrence of events of interest and estimate
the parameters of the events.
ī‚§Classify an object that has been detected.
ī‚§Track an object.
The technology for sensing and control includes electric
and magnetic field sensors; radio-wave frequency
sensors; optical-, electrooptic-, and infrared sensors;
radars; lasers; location and navigation sensors; seismic
and pressure-wave sensors; environmental parameter
sensors (e.g., wind, humidity, heat); and biochemical
national security–oriented sensors. Typical sensor
parameters (measurands) include:
īƒ˜Physical measurement.
īƒ˜Chemical and biological measurements.
īƒ˜Event measurement.
Hardware and Software
īƒ¨ Functions to be supported include:
īƒ¨ Intrinsic node functionality; signal processing,
including digital signal processing (e.g., FFT/DCT),
compression, forward error correction, and
encryption; control and actuation; clustering and in-
network computation; self-assembly;communication;
routing and forwarding; and connectivity
management.
DAWN Lab / UMBC 63
Hardware and Software
Sensors, particularly Smart Dust and COTS motes, have
four basic hardware subsystems:
1. Power: An appropriate energy infrastructure or supply
is necessary to support operation from a few hours to
months or years (depending on the application).
2. Computational logic and storage. These are used to
handle onboard data processing and manipulation,
transient and short-term storage, encryption, forward
error correction (FEC), digital modulation, and digital
transmission. WNs have computational requirements
typically ranging from an 8-bit microcontroller to a 64-
bit microprocessor. Storage requirements typically
range from 0.01 to 100 gigabytes (GB).
Hardware components of WNs
Hardware Subsystems
3.Sensor transducer(s). The interface between the
environment and the WN is the sensor. Basic
environmental sensors include, but are not limited to,
acceleration, humidity, light, magnetic flux,
temperature, pressure, and sound.
4. Communication. WNs must have the ability to
communicate either in and/or in C2WSN arrangements
C1WSN arrangements.
Softdware components of WNs
Software Subsystems
Sensors typically have five basic software subsystems:
1. Operating system (OS) microcode (also called
middleware).
2. Sensor drivers.
3. Communication processors.
4. Communication drivers (encoding and the physical
layer).
5. Data processing mini-apps.
Sensor Taxonomy
Sensor Taxonomy continued
Reduced-Complexity Taxonomy of Sensor Nodes
WN OPERATING ENVIRONMENT
In WSNs, physical connectivity is supported over a
wireless radio link of one or more hops, at a distance of
tens, hundreds, or thousand of meters. Logical
connectivity has the goal of supporting topology
maintenance and multihop routing (when present). :
Sensor nodes have to deal with the following resource
constraints:
īƒ˜Power consumption.
īƒ˜Communication.
īƒ˜Computation.
īƒ˜Uncertainty in measured parameters.
WN OPERATING ENVIRONMENT
Some of the intrinsic factors that the design constraints
or requirements that WSNs and WNs need to take into
account include the following:
â€ĸWNs may be deployed in a dense manner (close
proximity), implying communication complexity (e.g., in
support of packet forwarding and topology management)
â€ĸ For military and/or national security applications, WNs
need to support rapid deployment; the deployment must
be supportable in an ad hoc fashion; and the environment
is expected to be highly dynamic.
â€ĸWNs may be prone to failure. Unattended, untethered,
self-powered low-duty cycle systems are typical, yet
some WSNs require sensing systems that are long-lived
and environmentally resilient.
WN OPERATING ENVIRONMENT
â€ĸWNs are limited in power, computational capacity, and
memory. Communication circuitry and antennas are the primary
elements that use up most of the energy.
â€ĸThe topology that the WNs need to maintain may change very
frequently. Communication links may be expensive; the
bandwidth may be limited; the power availability at the sensor
may be limited and/or expensive in reference to supporting a high-
capacity, high-range link.
â€ĸWNs may not have global addresses because of the potentially
large number of sensors and overhead needed to support such
global addresses.
â€ĸWNs require special routing and data dissemination mechanisms.
WN OPERATING ENVIRONMENT
â€ĸWNs often require in-network processing, even while the data are
being routed. One wants to be able to perform data processing in
the network in the proximity of the source of the data, and then
forward only summarized,aggregated, fused, and/or synthesized
results. Typical functionality involves signal processing, data
aggregation, data fusion, and data analysis. There is also an
interest in database management, including querying mechanisms
and data storage and warehousing.
â€ĸ Arrays of ultralow-power wireless nodes may be incorporated in
reconfigurable networks with high-speed connectivity to
processing centers for decision and responsive action.
WN TRENDS
Evolving requirements for new WSNs and WNs include, among
others:
(1) The ability to respond to new toxic chemicals, explosives, and
biological agents;
(2) Enhanced sensitivity, selectivity, speed, robustness, and fewer
false alarms; and
(3) The ability to function, perhaps autonomously, in unusual,
extreme, and complex environments.
ī‚§Miniaturization, manufacturability, and cost are also critical
issues.
īƒ¨ Some of the goals are to develop mesoscale low-
cost (i.e., <50 cents) transceivers for ubiquitous
wireless data acquisition that minimize power or
energy dissipation [i.e., minimize energy (<5
nJ/(correct) bit)] for an energy-limited source and
minimize power (i.e., <100 mW for a power-limited
source, enabling energy scavenging) by using the
following strategies: selfconfiguring networks, an
integrated system-on-a-chip (SOC) approach, and
aggressive low-energy architectures and circuits.
77
īƒ¨ The application interface for WSNs should be an
abstraction that is offered to any sensor network
application and supported by any sensor network
platform.
īƒ¨ According to published reports, the U.S. Department
of Homeland Security (DHS) is coordinating an effort
for the end-of-decade deployment of a nationwide
sensor network to provide a real-time early-warning
system for a plethora of chemical, biological, and
nuclear threats across the United States.
78
īƒ¨ Sensors could use polymer- or gel-coated silicon
devices to trap targeted chemicals, then send the
agents through fluidic channels to on-chip arrays of
surface-acoustic-wave detectors.
īƒ¨ A follow-on device would integrate the fluidics,
surface acoustic waves, and support electronics on
a single device.
DAWN Lab / UMBC 79
IEEE 802.15.4, ZigBee
īļObjective of the IEEE 802.15.4 open standard is to support the
wireless connectivity of a vast number of industrial, home, and
medical applications, including automotive monitoring and control,
home automation, ubiquitous and pervasive health care, gaming, and
sensor-rich environments.
īļSuch applications require a small, low-cost, highly reliable
technology that offers long battery life, measured in months or even
years, and automatic or semiautomatic installation.
īļThe IEEE 802.15.4 standard supports these requirements by trading
off higher speed and performance for architectures that benefit from
low power consumption and low cost.
īļThe IEEE 802.15.4 standard has been adopted by the ZigBee Alliance
for wireless personal area network technology.
IEEE 802.15.4 and ZigBee reference model
ZigBee stack reference Model
īƒ¨ Using the IEEE 802.15.4 specifications, the alliance
focuses on the design issues related to the network,
security, and applications layers. It also provides
specification for interoperability and testing.
īƒ¨ The physical layer (PHY) of the reference model specifies
the network interface components, their parameters, and
their operation.
īƒ¨ Features of Physical Layer: Receiver energy detection
(RED), link quality indicator (LQI), and clear channel
assessment (CCA).
īƒ¨ The PHY layer is also specified with a wide range of
operational low-power features, including low-duty-cycle
operations, strict power management, and low
transmission overhead.
83
MAC Layer
īƒ¨ The MAC layer handles network association and
disassociation.
īƒ¨ It also regulates access to the medium. This is
achieved through two modes of operation:
beaconing and nonbeaconing.
īƒ¨ The beaconing mode is specified for environments
where control and data forwarding is achieved by an
always-active device.
īƒ¨ The nonbeaconing mode specifies the use of
unslotted, nonpersistent CSMA-based MAC
protocol.
84
Network Layer
īƒ¨ The network layer provides the functionality required
to support network configuration and device
discovery, association and disassociation, topology
management, MAC-layer management, routing, and
security management.
īƒ¨ Three network topologies—star, mesh, and cluster
tree—are supported.
85
Security Services by IEEE 8.2.15.4
īƒ¨ Support for access control using legitimate device.
īƒ¨ Message integrity protection
īƒ¨ Data confidentiality using AES, 128-bit
īƒ¨ Sequential data freshness to prevent replay attacks
īƒ¨ Using the basic security services, the MAC layer
describes a variety of security suites.
īƒ¨ By default, security is not enabled.
86
Application Layer
īƒ¨ The application layer consists of the application
support sublayer (APS), the ZigBee device object
(ZDO), and the manufacturer-defined application
objects.
īƒ¨ APS sublayer :Maintaining tables for binding
devices together, based on their services and their
needs, and forwarding messages between bound
devices.
īƒ¨ The ZDO can be thought of as a special application
object that is resident on all nodes. It has its own
profile, referred to as the ZigBee device profile
(ZDP), which user application endpoints and other
ZigBee nodes can access. 87
īƒ¨ The ZDO is responsible :
īƒ¨ Overall device management and security keys and
policies,
īƒ¨ including defining the role of the device within the
network, initiating and responding to binding requests,
and establishing a secure relationship between network
devices.
īƒ¨ The manufacturer-defined application objects implement
the actual applications according to the ZigBee-defined
application descriptions.
88
IEEE 802.15.4 PHY-layer operating frequency bands
The IEEE 802.15.4 standard defines three physical
media:
īƒ¨ Direct-sequence spread spectrum using BPSK
operating in the 868-MHz band at a data rate of 20
kbps.
īƒ¨ Direct-sequence spread spectrum using BPSK
operating in the 915-MHz band at a data rate of 40
kbps.
īƒ¨ Direct-sequence spread spectrum using O-QPSK
operating in the 2.4-GHz band at a data rate of 140
kbps.
90
īƒ¨ The chip modulation used by both specifications is BPSK
with raised cosine shaping .
īƒ¨ The resulting chip rate is 300 kilochips/sec for the 868-
MHz PHY layer and 600 kilochips/sec for the 915-MHz
PHY layer.
īƒ¨ The data modulation of the 2.4-GHz PHY layer is a 16-
ary orthogonal modulation. 16 symbols are an orthogonal
set of 32-chip PN codes.
īƒ¨ The resulting data rate is 250 kbps. The specification uses
O-QPSK with half-sine pulse shaping, which is equivalent
to minimum shift keying. The resulting chip rate is 2.0
megachips/sec.
91
IEEE 802.15.4 PHY-layer packet structure.
MAC Layer
īƒ¨ The IEEE 802.15.4 MAC-layer specification is
designed to support a vast number of industrial and
home applications for control and monitoring.
93
Features for flexible network configurations and low-power
operations :
īƒ¨ Support for various network topologies and network
devices
īƒ¨ The availability of an optional superframe structure to
control the network devices’ duty cycle
īƒ¨ Support for direct and indirect data transmissions
īƒ¨ Contention- and schedule-based media access control
methods
īƒ¨ Beaconed and nonbeaconed modes of operation
īƒ¨ Efficient energy management schemes for an extended
battery life, including adaptive sleep for extended period
of time over multiple beacons.
94
īƒ¨ Flexible addressing scheme to support the deployment of
large-scale networks, theoretically over 65,000 nodes per
network.
DAWN Lab / UMBC 95
Device Types and Network Topologies
To accommodate the MAC protocol, theIEEE 802.15.4 standard distinguishes
devices based on their hardware complexity and capability.
The standard defines two classes of physical devices:
â€ĸA full-function device (FFD) : It is equipped with the adequate resources and
memory capacity to handle all the functionalities and features specified by the
standard. It can therefore assume multiple network responsibilities. It can also
communicate with any other network device.
â€ĸA reduced-function device (RFD) : It is a simple device that carries a reduced
set of functionalities for lower cost and complexity. It typically contains a
physical interface to the wireless modem and executes the specified IEEE
802.15.4 MAC layer protocol. Furthermore, it can only associate and
communicate with an FFD.
ZigBee defines three types of logical devices:
â€ĸ Network coordinator
â€ĸ Router
â€ĸEnd devices
Based on these logical devices types, a ZigBee wireless personal
area network (PAN) can be organized in one of three possible
topologies: a star, a mesh (peer-to- peer), or a cluster tree.
98
Cluster Networks
īƒ¨ It enables a peer-to-peer network to be formed with
a minimum of routing overhead, using multihop
routing.
īƒ¨ The topology is suitable for latency-tolerant
applications.
īƒ¨ A cluster tree network is self-organized and supports
network redundancy to achieve a high degree of
fault resistance and self-repair.
īƒ¨ The cluster can be significantly large, comprising up
to 255 clusters of up to 254 nodes each, for a total
of 64,770 nodes.
99
īƒ¨ Any FFD can be a coordinator. Only one coordinator
is selected for the PAN.
īƒ¨ The PAN coordinator forms the first cluster and
assigns to it a cluster identity (CID) of value zero.
īƒ¨ Subsequent clusters are then formed with a
designated cluster head for each cluster.
īƒ¨ Each PAN is uniquely identified by a 16-bit identifier.
100
A coordinator is a network device configured to
support network functionalities and additional
responsibilities:
īƒ¨Managing a list of all associated network devices.
īƒ¨ Exchanging data frames with network devices and
a peer coordinator.
īƒ¨ Allocating 16-bit short addresses to network
devices.
īƒ¨Generating beacon frames on a periodic basis.
101
īƒ¨ The IEEE 802.15.4 MAC standard defines an optional
superframe structure. It is initiated by the PAN
coordinator.Its format is decided by the coordinator.
102
Superframe Structure
QoS frame structure
Superframe structure with energy saving
General MAC frame format
Beacon frame format
Data and acknowledgment frame format
MAC command frame format
Interframe spacing
Modes of Operation
The IEEE 802.15.4 MAC protocol is designed to meet the
requirements of multiple types of traffic. Each traffic type is
characterized by its unique characteristics in terms of the data
profile and latency requirement. Based on this characterization,
the IEEE 802.15.4 standard identifies three types of traffic:
â€ĸPeriodic data.
â€ĸIntermittent data.
â€ĸRepetitive low-latency data.
To accommodate three types of traffic, the IEEE 802.15.4 MAC-
layer standard specifies a beaconed and a beaconless mode of
operation.
Slotted CSMA algorithm
Unslotted CSMA algorithm
114
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WSN_Chapter _1.pptx

  • 1. Chapter -1 INTRODUCTION AND OVERVIEW OF WIRELESS SENSOR NETWORKS BY USHA PADMA Assistant Professor Telecommunication Department R V College of Engineering
  • 2. INTRODUCTION A sensor network is an infrastructure comprised of sensing (measuring), computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. There are four basic components in a sensor network: (1) an assembly of distributed or localized sensors; (2) an interconnecting network (usually, but not always, wireless-based); (3) a central point of information clustering; and (4) a set of computing resources at the central point (or beyond) to handle data correlation, event trending, status querying, and data mining.
  • 3. Background of Sensor Network Technology īƒ¨ The technology for sensing and control includes electric and magnetic field sensors;radio-wave frequency sensors; optical-, electrooptic-, and infrared sensors;radars; lasers; location/navigation sensors; seismic and pressure-wave sensors; environmental parameter sensors (e.g., wind, humidity, heat); and biochemical national security– oriented sensors. īƒ¨ Sensor devices, or wireless nodes (WNs), are also (sometimes) called motes. īƒ¨ A stated commercial goal is to develop complete microelectromechanical systems (MEMSs)–based sensor systems at a volume of 1 mm3
  • 4. Background of Sensor Network Technology īƒ¨ Within the sensor field, WSNs employ contention-oriented random- access channel sharing and transmission techniques that are now incorporated in the IEEE 802 family of standards. īƒ¨ AWSN consists of densely distributed nodes that support sensing, signal processing, embedded computing, and connectivity; sensors are logically linked by self organizing means (sensors that are deployed in short-hop point-to-point master–slave pair arrangements are also of interest). īƒ¨ WSNs have unique characteristics, such as power constraints and limited battery life for the WNs, redundant data acquisition, low duty cycle, and, many-to-one flows.
  • 5. Background of Sensor Network Technology īƒ¨ Sensors span several orders of magnitude in physical size; they (or, at least some of their components) range from nanoscopic-scale devices to mesoscopic-scale devices at one end, and from microscopic-scale devices to macroscopic-scale devices at the other end. īƒ¨ Embedded network sensing refers to the synergistic incorporation of microsensors in structures or environments; embedded sensing enables spatially and temporally dense monitoring of the system under consideration (e.g., an environment, a building, a battlefield).
  • 6. Background of Sensor Network Technology īƒ¨ Sensors facilitate the instrumenting and controlling of factories, offices, homes, vehicles, cities, and the ambiance, especially as commercial off-the-shelf technology becomes available. īƒ¨ A current research and development (R&D) challenge is to develop low-power communication with low-cost on-node processing and selforganizing connectivity/protocols; another critical challenge is the need for extended temporal operation of the sensing node despite a (typically) limited power supply (and/or battery life).
  • 7. Background of Sensor Network Technology īƒ¨ Power efficiency in WSNs is generally accomplished in three ways: 1. Low-duty-cycle operation. 2. Local/in-network processing to reduce data volume (and hence transmission time). 3. Multihop networking reduces the requirement for long-range transmission since signal path loss is an inverse exponent with range or distance. Each node in the sensor network can act as a repeater, thereby reducing the link range coverage required and, in turn, the transmission power.
  • 8. Background of Sensor Network Technology Sensor networks and systems are taxomised into two categories: īƒ¨ Category 1 WSNs (C1WSNs): almost invariably mesh-based systems with multihop radio connectivity among or between WNs, utilizing dynamic routing in both the wireless and wireline portions of the network. Military theater systems typically belong to this category. īƒ¨ Category 2 WSNs (C2WSNs): point-to-point or multipoint-to- point (starbased) systems generally with single-hop radio connectivity to WNs, utilizing static routing over the wireless network; typically, there will be only one route from the WNs to the companion terrestrial or wireline forwarding node (WNs are pendent nodes). Residential control systems typically belong to this category.
  • 9. Standardization of WSN â€ĸWithin building, Wi-Fi (IEEE 802.11b) was ruled out. â€ĸInfrared systems were not suitable. â€ĸ Bluetooth was too complex and expensive. â€ĸ IEEE 802.15.4 with ZigBee. â€ĸZigBee comprises the software layers above IEEE 802.15.4. â€ĸ IEEE 802.15.4 operates in 2.4 GHz ISM radio band. â€ĸ Data rate upto 250 kbps ranging from 30 to 200ft.
  • 10. Background of Sensor Network Technology īƒ¨ There is also considerable research in the area of mobile ad hoc networks (MANETs). WSNs are similar to MANETs in some ways; for example, both involve multihop communications. The applications and technical requirements for the two systems are significantly different in several respects DAWN Lab / UMBC 10
  • 11. Background of Sensor Network Technology īƒ¨ The typical mode of communication in WSN is from multiple data sources to a data recipient or sink (somewhat like a reverse multicast) rather than communication between a pair of nodes. In other words, sensor nodes use primarily multicast or broadcast communication, whereas most MANETs are based on point-to- point communications. īƒ¨ In most scenarios (applications) the sensors themselves are not mobile (although the sensed phenomena may be); this implies that the dynamics in the two types of networks are different. īƒ¨ Because the data being collected by multiple sensors are based on common phenomena, there is potentially a degree of redundancy in the data being communicated by the various sources in WSNs; this is not generally the case in MANETs.
  • 12. Background of Sensor Network Technology īƒ¨ Because the data being collected by multiple sensors are based on common phenomena, there is potentially some dependency on traffic event generation in WSNs, such that some typical random- access protocol models may be inadequate at the queueing-analysis level; this is generally not the case in MANETs. īƒ¨ A critical resource constraint in WSNs is energy; this is not always the case in MANETs, where the communicating devices handled by human users can be replaced or recharged relatively often. The scale of WSNs (especially, C1WSNs) and the necessity for unattended operation for periods reaching weeks or months implies that energy resources have to be managed very judiciously. This, in turn, precludes high-data-rate transmission. īƒ¨ The number of sensor nodes in a sensor network can be several orders of magnitude higher than the nodes in a MANET.
  • 13. Applications of Sensor Networks īƒ¨ Military applications. īƒ¨ Environmental applications. īƒ¨ Health applications. īƒ¨ Home applications. īƒ¨ Commercial applications. ī‚§ Smart spaces
  • 14. Basic Sensor Network Architectural Elements īƒ¨ These elements and design principles need to be placed in the context of the C1WSN sensor network environment, which is characterized by many (sometimes all) of the following factors: īƒ¨ Large sensor population īƒ¨ Large streams of data, īƒ¨ Incomplete/uncertain data, īƒ¨ High potential node failure; high īƒ¨ Potential link failure (interference), īƒ¨ Electrical power limitations, īƒ¨ Processing power Limitations, īƒ¨ Multihop topology, īƒ¨ Lack of global knowledge about the network, and īƒ¨ Limited administrative support for the network.
  • 15. Sensor Types and Technology A sensor network is composed of a large number of sensor nodes that are densely deployed. īƒ¨ Sensor nodes may be deployed in an open space; on a battlefield in front of, or beyond, enemy lines; in the interior of industrial machinery; at the bottom of a body of water; in a biologically and/or chemically contaminated field; in a commercial building; in a home; or in or on a human body. īƒ¨ Sensor nodes are scattered in a special domain called a sensor field. īƒ¨ Each of the distributed sensor nodes typically has the capability to collect data, analyze them, and route them to a (designated) sink point.
  • 16. Typical sensor network arrangement.
  • 17. īƒ¨ Embedded sensor networks are predicated on three supporting components: embedding, networking, and sensing. īƒ¨ Embedding implies the incorporation of numerous distributed devices to monitor the physical world and interact with it; the devices are untethered nodes of small form factors that are equipped with a control and communication subsystem. Spatially- and temporally-dense arrangements are common. īƒ¨ Networking implies the concept of physical and logical connectivity. Logical connectivity has the goal of supporting coordination and other high-level tasks; physical connectivity is typically supported over a wireless radio link. īƒ¨ Sensing implies the presence of these capabilities in a tightly coupled environment, typically for the measurement of physical- world parameters.
  • 18. Features of sensor networks īƒ¨ Sensor nodes are densely deployed. īƒ¨ Sensor nodes are prone to failures. īƒ¨ The topology of a sensor network changes very frequently. īƒ¨ Sensor nodes are limited in power, computational capacities, and memory. īƒ¨ Sensor nodes may not have global identification because of the large amount of overhead and the large number of sensors.
  • 20. īƒ¨ Sensor networks require sensing systems that are long- lived and environmentally resilient. Unattended, untethrered, self-powered low-duty-cycle systems are typical. īƒ¨ Sensors are either passive or active devices. īƒ¨ Passive sensors in element form include seismic-, acoustic-, strain-, humidity-, and temperature-measuring devices. They tend to be low-energy devices. īƒ¨ Active sensors include radar and sonar; these tend to be high-energy systems. The trend is toward VLSI (very large scale integration), integrated optoelectronics, and nanotechnology;
  • 21. īƒ¨ In addition to (embedded) sensing there is a desire to build, deploy, and manage unattended or untethered embedded control and actuation systems, sometimes called control networks. īƒ¨ Such a control system acts on the environment either in a self-autonomous manner or under the telemetry of a remote or centralized node. īƒ¨ Key applications require more than just sensing: They need control and actuation.
  • 22. Software (Operating Systems and Middleware) īƒ¨ To support the node operation, it is important to have open- source operating systems designed specifically for WSNs. īƒ¨ Such operating systems typically utilize a component-based architecture that enables rapid implementation and innovation while minimizing code size as required by the memory constraints endemic in sensor networks. īƒ¨ Tiny OS is one such example of a de facto standard, but not the only one. īƒ¨ Tiny OS’s component library includes network protocols, distributed services, sensor drivers, and data acquisition tools.
  • 23. Standards for Transport Protocols īƒ¨ The goal of WSN engineers is to develop a cost- effective standards-based wireless networking solution that supports low-to medium data rates, has low power consumption, and guarantees security and reliability.
  • 24. Generic Protocol Stack for Sensor networks īƒ¨ Combine power and routing awareness īƒ¨ Integrates data with networking protocols īƒ¨ Communicates power efficiently through the wireless medium īƒ¨ Promotes cooperative efforts among sensor nodes.
  • 25. Possible Lower –Layer WSN Protocols
  • 26. Physical layer: Communication channel, sensing , actuation and signal processing. Address the needs of simple but robust modulation, transmission, and receiving techniques. īƒ¨ frequency selection. īƒ¨ carrier frequency generation. īƒ¨ signal detection and propagation. īƒ¨ signal modulation and data encryption.
  • 27. Data link layer : The data link layer is responsible for the multiplexing of data stream, data frame detection, the medium access and error control. īƒ¨ Medium Access Control īƒ¨ Power Saving Modes of Operation īƒ¨ Error Control
  • 28. Network layer: īƒ¨ Power efficiency is always an important consideration. īƒ¨ Sensor networks are mostly data centric. īƒ¨ Data aggregation is useful only when it does not hinder the collaborative effort of the sensor nodes. īƒ¨ An ideal sensor network has attribute-based addressing and location awareness. īƒ¨ Adaptive topology management and topological routing.
  • 29. Transport layer: īƒ¨ This layer is especially needed when the system is planned to be accessed through Internet or other external networks. īƒ¨ TCP/UDP type protocols meet most requirements (not based on global addressing). īƒ¨ Data dissemination and accumulation, caching and storage.
  • 30. Upper layer: Management protocol makes the hardware and software of the lower layers transparent to the sensor network management applications. īƒ¨ Sensor management protocol (SMP) īƒ¨ Task assignment and data advertisement protocol (TADAP) īƒ¨ Sensor query and data dissemination protocol (SQDDP) īƒ¨ Application processing, data aggregation, external querying query processing, and external database.
  • 31. Routing and Data Dissemination Routing protocols for WSNs generally fall into three groups: īļ Data-centric : SPIN, GBR, CADR, Directed diffusion Rumor routing, etc. īļ Hierarchical : LEACH, TEEN, APTEEN, PEGASIS, etc. īļ Location-based :MECN, SMECN, GAF and GEAR. īļ QoS-oriented : SAR and SPEED. 31
  • 32. 32 Network Design Issues īƒ¨ Issues relate to reliable transport (possibly including encryption), bandwidth-and power limited transmission, data-centric routing, in-network processing, and self configuration. īƒ¨ Design factors include operating environment and hardware constraints such as transmission media, radio-frequency integrated circuits, power constraints, communications network interfaces; and network architecture and protocols, including network topology and fault tolerance, scalability, self-organization, and mobility.
  • 33. 33 Brief Historical Survey of Sensor Networks The history of sensor networks spans four phases: īƒ˜ Phase 1: Cold-War Era Military Sensor Networks. īƒ˜ Phase 2: Defense Advanced Research Projects Agency Initiatives. īƒ˜ Phase 3: Military Applications Developed or Deployed in the 1980s and 1990s. īƒ˜ Phase 4: Present-Day Sensor Network Research.
  • 34. Applications of WSN WSNs are collections of compact-size, relatively inexpensive computational nodes that measure local environmental conditions or other parameters and forward such information to a central point for appropriate processing. WSNs nodes (WNs) can sense the environment, can communicate with neighboring nodes, and can, in many cases, perform basic computations on the data being collected. WSNs support a wide range of useful applications.
  • 35. EXAMPLES OF CATEGORY 1 WSN APPLICATIONS Some examples of WSN applications are : īƒŧ Military sensor networks to detect and gain as much information as possible about enemy movements, explosions, and other phenomena of interest. īƒŧ Law enforcement and national security applications for inimical agent tracking or nefarious substance monitoring. īƒŧ Sensor networks to detect and characterize chemical, biological, radiological, nuclear, and explosive (CBRNE) attacks and material. īƒŧSensor networks to detect and monitor environmental changes in plains, forests, oceans, and so on.
  • 36. EXAMPLES OF CATEGORY 1 WSN APPLICATIONS īƒŧ Wireless traffic sensor networks to monitor vehicle traffic on highways or in congested parts of a city. īƒŧ Wireless surveillance sensor networks for providing security in shopping malls, parking garages, and other facilities. īƒŧWireless parking lot sensor networks to determine which spots are occupied and which are free. īƒŧBorders monitoring with sensors and satellite uplinks.
  • 37. Sensor and Robots Two technologies appear poised for a degree of convergence: mobile robotics and wireless sensor networks. The field of mobile robotics deals with mechanical aspects (the wheels, motors, grasping arms, or physical layout) as well as with the logic aspects. Two questions of interest are : īą Can a mobile robot act as a gateway into a wireless sensor network? īąCan sensor networks take advantage of a robot’s mobility and intelligence? To affect this convergence, inexpensive standards-based hardware, open-source operating systems, and off-the- shelf connectivity modules are required.
  • 39. Theme park WSN example
  • 40. Reconfigurable Sensor Networks Military applications require support for tactical and surveillance arrangements that employ reconfigurable sensor WNs that are capable of forming networks on the fly, assembling themselves without central control, and being deployed incrementally. Reconfigurable ‘‘smart’’ WNs are self-aware, self-configurable, and autonomous. Self-organizing WSNs utilize mechanisms that allow newly deployed WNs to establish connectivity (to build up a network topology) spontaneously. Also, these networks have mechanisms for managing WN mobility (if any), WN reconfiguration, and WN failure.
  • 41. Highway Monitoring ī‚§Transportation (traffic flow) is a sector that is expected to benefit from increased monitoring and surveillance. ī‚§The system is installed along major highways; the digital sensor network gathers lane-by-lane data on travel speeds, lane occupancy, and vehicle counts. These basic data elements make it possible to calculate average speeds and travel times. The data are then transmitted to the data center for reformatting. The network monitors roadway conditions continuously on a 24/7 basis and provides updates to the data center in real time. The system collects key traffic information, including vehicle speeds, counts (volume), and roadway density, transmitting the data over a wireless network to a data center every 60 seconds.
  • 42. Highway Monitoring Applications include the following: 1. Private traffic information providers in the United States: The company’s realtime and archived data offer valuable tools for a variety of commercial and governmental applications. 2. Telematics: For mobile professionals and others, the company’s traffic information complements in-vehicle navigation devices, informing drivers not only how to get from point A to point B but how long it will take to get there, or even direct them to an alternative route.
  • 43. Military Applications Wireless distributed microsensor networks consist of a collection of communicating nodes, where each node incorporates: (1) One or more sensors for measuring the environment. (2) Computing capability to process sensor data into ‘‘high- value’’ information and to accomplish local control, and (3) A radio to communicate information to and from neighboring nodes and eventually to external users.
  • 44. Civil and Environmental Engineering Applications īƒ˜Sensors can be used for civil engineering applications. īƒ˜The goal is to develop ‘‘smart structures’’ that are able to self-diagnose potential problems and self-prioritize requisite repairs(earthquake active zones). īƒ˜The battery-powered matchbox-sized WNs operating on Tiny OS are designed to sense a number of factors, ranging from light and temperature (for energy-saving applications) to dynamic response (for civil engineering analysis).
  • 45. Wildfire Instrumentation īļCollecting real-time data from wildfires is important for life safety considerations and allows predictive analysis of evolving fire behavior. īļOne way to collect such data is to deploy sensors in the wildfire environment. FireBugs are small wireless sensors (motes) based on TinyOS that self-organize into networks for collecting real-time data in wildfire environments. īļThe FireBug system combines state-of-the-art sensor hardware running TinyOS with standard off-the-shelf World Wide Web and database technology, allowing rapid deployment of sensors and behavior monitoring.
  • 46. Habitat Monitoring īļThe goal was to develop a habitat-monitoring kit that enables researchers worldwide to engage in nonintrusive and nondisruptive monitoring of sensitive wildlife and habitats. īļAbout three dozen motes were deployed onthe island. Each mote has a microcontroller, a low-power radio, memory, and batteries. īļSensor motes monitor the nesting habitat of Leach’s storm petrel on the island and relay their readings into a satellite link that allows researchers to download real- time environmental data over the Internet. īļFor habitat monitoring the planner needed sensors that can take readings for temperature, humidity, barometric pressure, and midrange infrared. Motes sample and relay their sensor readings periodically to computer base
  • 47. Nanoscopic Sensor Applications ī‚§There is interest in the ‘‘labs on a chip’’ concept, including new methodologies supported by nanotechniques. ī‚§In particular, a nanoscopic microscale confocal imaging array (micro-CIA) is a device that merges MEMSs (micro electromechanical systems), ultrasmall lasers, lenses, and plumbing. ī‚§These devices are fabricated by micromachining silicon or polymers. Using this technology, one can detect biowarfare pathogens and can use it as a diagnostic tool in medicine.
  • 49. ANOTHER TAXONOMY OF WSN TECHNOLOGY Three types of WSN system (technology) are: 1. Nonpropagating WSN systems 2. Deterministic routing WSN systems a. Aggregating b. Nonaggregating systems 3. Self-configurable and self-organizing WSN systems a. Aggregating b. Nonaggregating systems
  • 50. EXAMPLES OF CATEGORY 2 WSN APPLICATIONS C2WSN technology is being targeted for a gamut of building automation, industrial, medical, residential control, and monitoring applications. Many of these applications are being contemplated in the context of the IEEE 802.15.4 (ZigBee) standard solution. Examples of applications include lighting controls; automatic meter reading;wireless smoke and CO detectors; HVAC control; heating control; home security; environmental controls; blind, drapery, and shade controls; medical sensing and monitoring; universal remote control to a set-top box that includes home control, industrial automation, and building automation. īļ Home Control
  • 51. īƒ¨ Zigbee is designed for low to very –low –duty cycle static and dynamic environments with many active nodes. īƒ¨ Bluetooth is designed for high QOS, a variety of duty cycles, and moderate data rates in networks with limited active nodes. īƒ¨ Battery arrangement based on two AA alkaline cells or one Li-AA cell. īƒ¨ Oscillator wake up the main processor. īƒ¨ Security systems, 10 seconds to 15 minutes. 51
  • 53. Home Control Home control applications provide control, conservation, convenience, and safety, as follows: īļSensing applications facilitate flexible management of lighting, heating, and cooling systems from anywhere in the home. īļ Sensing applications automate control of multiple home systems to improve conservation, convenience, and safety. īļ Sensing applications capture highly detailed electric, water, and gas utility usage data. īļSensing applications embed intelligence to optimize consumption of natural resources.
  • 54. Home Control continued īļSensing applications enable the installation, upgrading, and networking of a home control system without wires. īļ Sensing applications enable one to configure and run multiple systems from a single remote control. īļ Sensing applications support the straightforward installation of wireless sensors to monitor a wide variety of conditions. īļ Sensing applications facilitate the reception of automatic notification upon detection of unusual events.
  • 55. Medical Applications A number of hospitals and medical centers are exploring applications of WSN technology to a range of medical applications, including pre-hospital and in-hospital emergency care, disaster response, and stroke patient rehabilitation. WSNs have the potential to affect the delivery and study of resuscitative care by allowing vital signs to be collected and integrated automatically into the patient care record and used for real-time triage, correlation with hospital records, and long-term observation. WSNs permit home monitoring for chronic and elderly patients, facilitating long-term care and trend analysis. WSNs also permit collection of long-term medical information that populates databases of clinical data; this enables longitudinal studies across populations and allows physicians to study the effects of medical intervention programs.
  • 56. īƒ¨ Harvard University and others have developed a small, wearable wireless pulse oximeter and two- lead electrocardiogram (EKG). īƒ¨ The data can be displayed in real time and integrated into developing pre-hospital patient care record. īƒ¨ The sensor devices themselves can be programmed to process the vital sign data. 56
  • 57. īƒ¨ In collaboration with the Motion Analysis Laboratory at the Spaulding Rehabilitation Hospital, Harvard University has also developed a tiny wearable device for monitoring the limb movements and muscle activity of stroke patients during rehabilitation exercise. īƒ¨ These devices, consisting of three-axis accelerometer, gyroscope, and electromyogram sensors, allow researchers to capture a rich data set of motion data for studying the effect of various rehabilitation exercises on this patient population. 57
  • 58. īƒ¨ In addition to the hardware platform, Harvard University developed a scalable software infrastructure called CodeBlue, for wireless medical devices. īƒ¨ CodeBlue is designed to provide routing, naming, discovery, and security for wireless medical sensors, PDAs, PCs, and other devices that may be used to monitor and treat patients in a number of medical settings. īƒ¨ CodeBlue is designed to scale across a different network densities, ranging from sparse clinic and hospital deployments to very dense ad hoc deployments at a mass casualty site. īƒ¨ Part of the CodeBlue system includes a system for tracking the location of individual patient devices indoors and outdoors using radio signal information. 58
  • 59. Use of CodeBlue for emergency response 59
  • 60. Basic Wireless Sensor Technology Introduction WSNs are characterized by the fact that they need to operate in resource-constrained environments; in turn, this fact imposes strict design guidelines and limitations on the WNs. sensor functionality and components, including the sensing and actuation unit, processing unit, communication unit, power unit, and other application- dependent units are addressed.
  • 61. SENSOR NODE TECHNOLOGY At the design level a WSN sits at the confluence of research in disciplines such as database query processing, networking, algorithms, and distributed systems. The basic functionality of a WN generally depends on the application, but the following requirements are typical : ī‚§Determine the value of a parameter at a given location. ī‚§Detect the occurrence of events of interest and estimate the parameters of the events. ī‚§Classify an object that has been detected. ī‚§Track an object.
  • 62. The technology for sensing and control includes electric and magnetic field sensors; radio-wave frequency sensors; optical-, electrooptic-, and infrared sensors; radars; lasers; location and navigation sensors; seismic and pressure-wave sensors; environmental parameter sensors (e.g., wind, humidity, heat); and biochemical national security–oriented sensors. Typical sensor parameters (measurands) include: īƒ˜Physical measurement. īƒ˜Chemical and biological measurements. īƒ˜Event measurement.
  • 63. Hardware and Software īƒ¨ Functions to be supported include: īƒ¨ Intrinsic node functionality; signal processing, including digital signal processing (e.g., FFT/DCT), compression, forward error correction, and encryption; control and actuation; clustering and in- network computation; self-assembly;communication; routing and forwarding; and connectivity management. DAWN Lab / UMBC 63
  • 64. Hardware and Software Sensors, particularly Smart Dust and COTS motes, have four basic hardware subsystems: 1. Power: An appropriate energy infrastructure or supply is necessary to support operation from a few hours to months or years (depending on the application). 2. Computational logic and storage. These are used to handle onboard data processing and manipulation, transient and short-term storage, encryption, forward error correction (FEC), digital modulation, and digital transmission. WNs have computational requirements typically ranging from an 8-bit microcontroller to a 64- bit microprocessor. Storage requirements typically range from 0.01 to 100 gigabytes (GB).
  • 66. Hardware Subsystems 3.Sensor transducer(s). The interface between the environment and the WN is the sensor. Basic environmental sensors include, but are not limited to, acceleration, humidity, light, magnetic flux, temperature, pressure, and sound. 4. Communication. WNs must have the ability to communicate either in and/or in C2WSN arrangements C1WSN arrangements.
  • 68. Software Subsystems Sensors typically have five basic software subsystems: 1. Operating system (OS) microcode (also called middleware). 2. Sensor drivers. 3. Communication processors. 4. Communication drivers (encoding and the physical layer). 5. Data processing mini-apps.
  • 72. WN OPERATING ENVIRONMENT In WSNs, physical connectivity is supported over a wireless radio link of one or more hops, at a distance of tens, hundreds, or thousand of meters. Logical connectivity has the goal of supporting topology maintenance and multihop routing (when present). : Sensor nodes have to deal with the following resource constraints: īƒ˜Power consumption. īƒ˜Communication. īƒ˜Computation. īƒ˜Uncertainty in measured parameters.
  • 73. WN OPERATING ENVIRONMENT Some of the intrinsic factors that the design constraints or requirements that WSNs and WNs need to take into account include the following: â€ĸWNs may be deployed in a dense manner (close proximity), implying communication complexity (e.g., in support of packet forwarding and topology management) â€ĸ For military and/or national security applications, WNs need to support rapid deployment; the deployment must be supportable in an ad hoc fashion; and the environment is expected to be highly dynamic. â€ĸWNs may be prone to failure. Unattended, untethered, self-powered low-duty cycle systems are typical, yet some WSNs require sensing systems that are long-lived and environmentally resilient.
  • 74. WN OPERATING ENVIRONMENT â€ĸWNs are limited in power, computational capacity, and memory. Communication circuitry and antennas are the primary elements that use up most of the energy. â€ĸThe topology that the WNs need to maintain may change very frequently. Communication links may be expensive; the bandwidth may be limited; the power availability at the sensor may be limited and/or expensive in reference to supporting a high- capacity, high-range link. â€ĸWNs may not have global addresses because of the potentially large number of sensors and overhead needed to support such global addresses. â€ĸWNs require special routing and data dissemination mechanisms.
  • 75. WN OPERATING ENVIRONMENT â€ĸWNs often require in-network processing, even while the data are being routed. One wants to be able to perform data processing in the network in the proximity of the source of the data, and then forward only summarized,aggregated, fused, and/or synthesized results. Typical functionality involves signal processing, data aggregation, data fusion, and data analysis. There is also an interest in database management, including querying mechanisms and data storage and warehousing. â€ĸ Arrays of ultralow-power wireless nodes may be incorporated in reconfigurable networks with high-speed connectivity to processing centers for decision and responsive action.
  • 76. WN TRENDS Evolving requirements for new WSNs and WNs include, among others: (1) The ability to respond to new toxic chemicals, explosives, and biological agents; (2) Enhanced sensitivity, selectivity, speed, robustness, and fewer false alarms; and (3) The ability to function, perhaps autonomously, in unusual, extreme, and complex environments. ī‚§Miniaturization, manufacturability, and cost are also critical issues.
  • 77. īƒ¨ Some of the goals are to develop mesoscale low- cost (i.e., <50 cents) transceivers for ubiquitous wireless data acquisition that minimize power or energy dissipation [i.e., minimize energy (<5 nJ/(correct) bit)] for an energy-limited source and minimize power (i.e., <100 mW for a power-limited source, enabling energy scavenging) by using the following strategies: selfconfiguring networks, an integrated system-on-a-chip (SOC) approach, and aggressive low-energy architectures and circuits. 77
  • 78. īƒ¨ The application interface for WSNs should be an abstraction that is offered to any sensor network application and supported by any sensor network platform. īƒ¨ According to published reports, the U.S. Department of Homeland Security (DHS) is coordinating an effort for the end-of-decade deployment of a nationwide sensor network to provide a real-time early-warning system for a plethora of chemical, biological, and nuclear threats across the United States. 78
  • 79. īƒ¨ Sensors could use polymer- or gel-coated silicon devices to trap targeted chemicals, then send the agents through fluidic channels to on-chip arrays of surface-acoustic-wave detectors. īƒ¨ A follow-on device would integrate the fluidics, surface acoustic waves, and support electronics on a single device. DAWN Lab / UMBC 79
  • 80. IEEE 802.15.4, ZigBee īļObjective of the IEEE 802.15.4 open standard is to support the wireless connectivity of a vast number of industrial, home, and medical applications, including automotive monitoring and control, home automation, ubiquitous and pervasive health care, gaming, and sensor-rich environments. īļSuch applications require a small, low-cost, highly reliable technology that offers long battery life, measured in months or even years, and automatic or semiautomatic installation. īļThe IEEE 802.15.4 standard supports these requirements by trading off higher speed and performance for architectures that benefit from low power consumption and low cost. īļThe IEEE 802.15.4 standard has been adopted by the ZigBee Alliance for wireless personal area network technology.
  • 81. IEEE 802.15.4 and ZigBee reference model
  • 83. īƒ¨ Using the IEEE 802.15.4 specifications, the alliance focuses on the design issues related to the network, security, and applications layers. It also provides specification for interoperability and testing. īƒ¨ The physical layer (PHY) of the reference model specifies the network interface components, their parameters, and their operation. īƒ¨ Features of Physical Layer: Receiver energy detection (RED), link quality indicator (LQI), and clear channel assessment (CCA). īƒ¨ The PHY layer is also specified with a wide range of operational low-power features, including low-duty-cycle operations, strict power management, and low transmission overhead. 83
  • 84. MAC Layer īƒ¨ The MAC layer handles network association and disassociation. īƒ¨ It also regulates access to the medium. This is achieved through two modes of operation: beaconing and nonbeaconing. īƒ¨ The beaconing mode is specified for environments where control and data forwarding is achieved by an always-active device. īƒ¨ The nonbeaconing mode specifies the use of unslotted, nonpersistent CSMA-based MAC protocol. 84
  • 85. Network Layer īƒ¨ The network layer provides the functionality required to support network configuration and device discovery, association and disassociation, topology management, MAC-layer management, routing, and security management. īƒ¨ Three network topologies—star, mesh, and cluster tree—are supported. 85
  • 86. Security Services by IEEE 8.2.15.4 īƒ¨ Support for access control using legitimate device. īƒ¨ Message integrity protection īƒ¨ Data confidentiality using AES, 128-bit īƒ¨ Sequential data freshness to prevent replay attacks īƒ¨ Using the basic security services, the MAC layer describes a variety of security suites. īƒ¨ By default, security is not enabled. 86
  • 87. Application Layer īƒ¨ The application layer consists of the application support sublayer (APS), the ZigBee device object (ZDO), and the manufacturer-defined application objects. īƒ¨ APS sublayer :Maintaining tables for binding devices together, based on their services and their needs, and forwarding messages between bound devices. īƒ¨ The ZDO can be thought of as a special application object that is resident on all nodes. It has its own profile, referred to as the ZigBee device profile (ZDP), which user application endpoints and other ZigBee nodes can access. 87
  • 88. īƒ¨ The ZDO is responsible : īƒ¨ Overall device management and security keys and policies, īƒ¨ including defining the role of the device within the network, initiating and responding to binding requests, and establishing a secure relationship between network devices. īƒ¨ The manufacturer-defined application objects implement the actual applications according to the ZigBee-defined application descriptions. 88
  • 89. IEEE 802.15.4 PHY-layer operating frequency bands
  • 90. The IEEE 802.15.4 standard defines three physical media: īƒ¨ Direct-sequence spread spectrum using BPSK operating in the 868-MHz band at a data rate of 20 kbps. īƒ¨ Direct-sequence spread spectrum using BPSK operating in the 915-MHz band at a data rate of 40 kbps. īƒ¨ Direct-sequence spread spectrum using O-QPSK operating in the 2.4-GHz band at a data rate of 140 kbps. 90
  • 91. īƒ¨ The chip modulation used by both specifications is BPSK with raised cosine shaping . īƒ¨ The resulting chip rate is 300 kilochips/sec for the 868- MHz PHY layer and 600 kilochips/sec for the 915-MHz PHY layer. īƒ¨ The data modulation of the 2.4-GHz PHY layer is a 16- ary orthogonal modulation. 16 symbols are an orthogonal set of 32-chip PN codes. īƒ¨ The resulting data rate is 250 kbps. The specification uses O-QPSK with half-sine pulse shaping, which is equivalent to minimum shift keying. The resulting chip rate is 2.0 megachips/sec. 91
  • 92. IEEE 802.15.4 PHY-layer packet structure.
  • 93. MAC Layer īƒ¨ The IEEE 802.15.4 MAC-layer specification is designed to support a vast number of industrial and home applications for control and monitoring. 93
  • 94. Features for flexible network configurations and low-power operations : īƒ¨ Support for various network topologies and network devices īƒ¨ The availability of an optional superframe structure to control the network devices’ duty cycle īƒ¨ Support for direct and indirect data transmissions īƒ¨ Contention- and schedule-based media access control methods īƒ¨ Beaconed and nonbeaconed modes of operation īƒ¨ Efficient energy management schemes for an extended battery life, including adaptive sleep for extended period of time over multiple beacons. 94
  • 95. īƒ¨ Flexible addressing scheme to support the deployment of large-scale networks, theoretically over 65,000 nodes per network. DAWN Lab / UMBC 95
  • 96. Device Types and Network Topologies To accommodate the MAC protocol, theIEEE 802.15.4 standard distinguishes devices based on their hardware complexity and capability. The standard defines two classes of physical devices: â€ĸA full-function device (FFD) : It is equipped with the adequate resources and memory capacity to handle all the functionalities and features specified by the standard. It can therefore assume multiple network responsibilities. It can also communicate with any other network device. â€ĸA reduced-function device (RFD) : It is a simple device that carries a reduced set of functionalities for lower cost and complexity. It typically contains a physical interface to the wireless modem and executes the specified IEEE 802.15.4 MAC layer protocol. Furthermore, it can only associate and communicate with an FFD.
  • 97. ZigBee defines three types of logical devices: â€ĸ Network coordinator â€ĸ Router â€ĸEnd devices Based on these logical devices types, a ZigBee wireless personal area network (PAN) can be organized in one of three possible topologies: a star, a mesh (peer-to- peer), or a cluster tree.
  • 98. 98
  • 99. Cluster Networks īƒ¨ It enables a peer-to-peer network to be formed with a minimum of routing overhead, using multihop routing. īƒ¨ The topology is suitable for latency-tolerant applications. īƒ¨ A cluster tree network is self-organized and supports network redundancy to achieve a high degree of fault resistance and self-repair. īƒ¨ The cluster can be significantly large, comprising up to 255 clusters of up to 254 nodes each, for a total of 64,770 nodes. 99
  • 100. īƒ¨ Any FFD can be a coordinator. Only one coordinator is selected for the PAN. īƒ¨ The PAN coordinator forms the first cluster and assigns to it a cluster identity (CID) of value zero. īƒ¨ Subsequent clusters are then formed with a designated cluster head for each cluster. īƒ¨ Each PAN is uniquely identified by a 16-bit identifier. 100
  • 101. A coordinator is a network device configured to support network functionalities and additional responsibilities: īƒ¨Managing a list of all associated network devices. īƒ¨ Exchanging data frames with network devices and a peer coordinator. īƒ¨ Allocating 16-bit short addresses to network devices. īƒ¨Generating beacon frames on a periodic basis. 101
  • 102. īƒ¨ The IEEE 802.15.4 MAC standard defines an optional superframe structure. It is initiated by the PAN coordinator.Its format is decided by the coordinator. 102
  • 105. Superframe structure with energy saving
  • 106. General MAC frame format
  • 108. Data and acknowledgment frame format
  • 109. MAC command frame format
  • 111. Modes of Operation The IEEE 802.15.4 MAC protocol is designed to meet the requirements of multiple types of traffic. Each traffic type is characterized by its unique characteristics in terms of the data profile and latency requirement. Based on this characterization, the IEEE 802.15.4 standard identifies three types of traffic: â€ĸPeriodic data. â€ĸIntermittent data. â€ĸRepetitive low-latency data. To accommodate three types of traffic, the IEEE 802.15.4 MAC- layer standard specifies a beaconed and a beaconless mode of operation.