UNIT II

SENSOR NETWORKS – INTRODUCTION & ARCHITECTURES

Challenges for Wireless Sensor Networks, Enabling Technologies for Wireless Sensor
Networks, WSN application examples, Single-Node Architecture – Hardware Components,
Energy Consumption of Sensor Nodes, Network Architecture – Sensor Network Scenarios,
Transceiver Design Considerations, Optimization Goals and Figures of Merit.

CHALLENGES FOR WIRELESS SENSOR NETWORKS:

For handling wide range of applications, WSN should have the following characteristics.
Realizing these characteristics with new mechanisms is the major challenge of the vision of
wireless sensor networks.

1. Characteristic Requirements

(i)Type of Service (ii) Quality of Service

(iii)Fault tolerance (iv) Life time

(v) Scalability (vi) Wide range of densities

(vii)Programmability (viii) Maintainability

(i)Type of Service

• The conventional communication network simply moves the bits from one place to
another. But the WSN is expected to provide a meaningful information or actions
about a given task.

(ii)Quality of Service

• Ttraditional quality of service like delay or bandwidth are irrelevant when

applications are tolerant to latency.

• When actuators are to be controlled in a real-time fashion by the sensor network,

delay is important.

• When the amount and quality of information is needed, the packet delivery ratio is not
important.

(iii)Fault tolerance

• When the wireless communication between two nodes are damaged or permanently
interrupted, then the WSN should be able to tolerate such faults.

• To tolerate node failure, redundant deployment is necessary

(iv)Scalability
 • When WSN includes a large number of nodes, the employed architectures and
protocols must be able scale to these numbers.

(v)Lifetime

• Nodes will have only limited supply of energy (using batteries).Replacing these
energy sources in the field is usually not practicable. So WSN must operate at least
for a given mission time or as long as possible.

• A power source like solar cells might also be available on a sensor node.

• The lifetime of a network also has direct trade-offs against quality of service:
investing more energy can increase quality but decrease lifetime.

(vi)Wide range of densities

• In a WSN, the density of the network is the number of nodes per unit.

• Different applications will have very different node densities.

• Density can vary over time and space because nodes fail or move.

(vii)Programmability

• When there is in need of new task, these nodes should be programmable .The nodes

should be flexible while changing their task.

(viii)Maintainability

• WSN has to adapt to changes, self-monitoring and adapt operation

• WSN has to monitor its own health and status to change operational parameters or to
choose different trade-offs (e.g. to provide lower quality when energy resource
become scarce).

• WSN has to maintain itself and able to interact with external maintenance
mechanisms to ensure its extended operation at a required quality

2. Required Mechanism

(i)Multi hop Wireless Communication

(ii)Energy efficient operation

(iii)Auto Configuration

(iv)Collaboration and in network Configuration

(v)Data centric

(vi)Locality

(vii)Exploit trade offs

 (i)Multi hop Wireless Communication

• In wireless communication, a direct communication between a sender and a receiver

is faced with limitations.

• Long distance communication needs high transmission power.

• The use of intermediate nodes as relays can reduce the total required power.
Hence,for WSN, multihop communication will be a necessary ingredient.

(ii)Energy-efficient operation

• To support long lifetimes, energy-efficient data transport between nodes are needed
and it is measured in J/Bit.

• Also, nonhomogeneous energy consumption – the forming of “hotspots” – is an issue.

(iii)Auto-configuration

• A WSN will have to configure most of its operational parameters autonomously,

independent of external configuration

• Nodes should be able to determine their geographical positions only using other nodes
of the network – so called “self-location”.

• The network should be able to tolerate failing nodes (because of a depleted battery,
for example) or to integrate new nodes (because of incremental deployment after
failure, for example).

(iv)Collaboration and in-network processing

• In some applications, several sensors have to collaborate to detect an event for

providing enough information.

• Every node transmits all data to an external network and process it “at the edge” of
the network.

• An example is to determine the highest or the average temperature within an area

• Data centric

• Traditional communication networks are typically centered around the transfer

of data between two specific devices, each equipped with (at least) one
network address – the operation of such networks is thus address-centric.

• In WSN , the answers and values themselves are important , not which node
has provided them. Hence, switching from an address-centric paradigm to a
data-centric paradigm in designing architecture and communication protocols
is promising.

• An example for such a data-centric interaction would be to request the average

temperature in a given location area
(vi)Locality

• Nodes, which are very limited in resources like memory, should attempt to limit the
state that they accumulate during protocol processing to only information about their
direct neighbors.

(vii)Exploit trade-offs

• Higher energy expenditure allows higher result accuracy

• Longer lifetime of the entire network trades off against lifetime of individual nodes.

• Depending on application, deployment, and node failures at runtime, the density of

the network can change considerably .

ENABLING TECHNOLOGIES FOR WIRELESS SENSOR NETWORKS :

Building wireless sensor networks has only become possible with some fundamental
advances in enabling technologies.

Miniaturization of hardware:

First and foremost, among these technologies is the miniaturization of hardware. Smaller
feature sizes in chips have less power consumption of the basic components of a sensor node.

This is particularly relevant to microcontrollers and memory chips as such, but also, the radio
modems, responsible for wireless communication, have become much more energy efficient.
Reduced chip size and improved energy efficiency is accompanied by reduced cost, which is
necessary to make redundant deployment of nodes.

Sensing Equipment

The actual sensing equipment is the third relevant technology. However, it is difficult to
generalize because of the vast range of possible sensors. The basic parts of a sensor node
have to accompanied by power supply.

This requires, depending on application, high capacity batteries that last for long times
battery having negligible self-discharge rate, and that can efficiently provide small amounts
of current. Ideally, a sensor node also has a device for energy scavenging, recharging the
battery with energy gathered from the environment.Eg Solar cells or vibration-based power
generation. Such a concept requires the battery to be efficiently chargeable with small
amounts of current, which is not a standard ability. The counterpart to the basic hardware
technologies is software. The division of tasks and functionalities in a single node is done by
the architecture of the operating system or runtime environment. This environment has to
support simple retasking, cross-layer information exchange, and modularity to allow for
simple maintenance. This software architecture on a single node has to be extended to
structure interfaces for application programmers.
APPLICATIONS OF WSN:

1. Disaster relief applications

2. Environment control

3. Bio diversity Mapping

4. Intelligent buildings

5. Facility management

6. Precision agriculture

7. Medicine and health care

8. Logistics

9. Telematics

Disaster relief applications:

• Important application is wildfire detection.

• Sensor nodes are equipped with thermometers and can determine their own location .

• These sensors are deployed over a wildfire, for example, a forest, from an airplane.

• They collectively produce a “temperature map” of the area or determine the perimeter
of areas with high temperature that can be accessed from the outside by firefighters
equipped with Personal Digital Assistants (PDAs).

• Control of accidents in chemical factories.

• In military applications, where sensors should detect enemy troops .

• Sensors should be cheap ,enough and disposable .

Environment control:

• WSNs can be used to control the environment, for example, with respect to chemical
pollutants – a possible application is garbage dump sites.
 • For the construction of offshore wind farms ,WSN is used in the surveillance of the
marine ground floor to understand the erosion processes

Biodiversity mapping:

• WSNs is used to gain an understanding of the number of plant and animal species
that live in a given habitat (biodiversity mapping).

• WSNs are the long-term, unattended, wirefree operation of sensors close to the
objects that have to be observed

• Sensors can be made small enough which they negligibly disturb the observed
animals and plants.

• Life time of sensor is highly required.

Intelligent buildings:

• Buildings waste more amounts of energy by inefficient Humidity, Ventilation and Air
Conditioning (HVAC) usage.

• WSN is used to monitor the temperature, airflow, humidity, and other physical
parameters in a building

• This increase the comfort level of inhabitants and reduce the energy consumption

• Improved energy efficiency as well as improved convenience are some goals of

“intelligent buildings”.

• WSN can be used to monitor mechanical stress levels of buildings in seismically

active zones.

• It is used to measure the bending load of girders to know whether it is still safe to
enter a given building after an earthquake or whether the building is on the brink of
collapse .

• Similar systems can be applied to bridges.

• Sensors are used in detecting people enclosed in a collapsed building and

communicating such information to a rescue team.
 • Cost is relatively modest.

Facility management:

• Keyless entry applications,WSN is used to check which person(wear badge) is

allowed to enter which areas of a larger company site

• WSN is used to detect the intruders, for example of vehicles that pass a street outside
of normal business hours.

• WSN could track a vehicle’s position and alert security personnel.

• WSN could be used in a chemical plant to scan for leaking chemicals.

Challenging requirements for these applications are

• Large number of sensors

• Should be able to collaborate (e.g. in the tracking example)

They should be able to operate a long time on batteries.

Machine surveillance and preventive maintenance:

• Sensor nodes are used to detect the vibration patterns that indicate the need for
maintenance.

• Examples for such machinery could be robotics or the axles of trains for eg tire
pressure monitoring

• The main advantage of WSNs is the cable free operation, avoiding a maintenance
problem in itself and allowing a cheap, often retrofitted installation of such sensors.

• Sensors should have long battery power since exchanging batteries is usually
impractical and costly.
Precision agriculture:

• Applying WSN to agriculture allows precise irrigation and fertilizing by placing

humidity/soil composition sensors into the fields.

• One sensor per 100 m × 100 m area.

• Similarly, pest control can profit from a high-resolution surveillance of farm land.

• Sensor is attached to each pig or cow, which controls the health status of the animal
(by checking body temperature, step counting, or similar means) and raises alarms if
given thresholds are exceeded.

Medicine and health care:

• Sensors are directly attached to elderly patients for surveillance

• No cable is an advantage

• Automatic drug administration (embedding sensors into drug packaging, raising

alarms when applied to the wrong patient, is conceivable).

• Also, patient and doctor tracking systems within hospitals can be literally life saving.

Logistics:

• A simple RFID tag cannot support more advanced applications.

• It is very difficult to imagine how a passive system can be used to locate an item in a
warehouse

• It can also not easily store information about the history of its attached object

• Hence sensors are used to track the parcels during transportation or in warehouses.

Telematics:

• Sensors are embedded in the streets or roadsides and gather information about traffic
conditions

• This “intelligent roadside” could also interact with the cars to exchange danger
warnings about road conditions or traffic jams ahead.

SINGLE-NODE ARCHITECTURE:

The five main components of sensor node are

1. Controller

2. Communication devices
 3. Sensors and Actuators

4. Memory

5. Power supply

• Controller -A controller is used to process all the relevant data, capable of executing
arbitrary code.

• Memory -Different types of memory are used to store programs and data.

• Sensors and actuators The actual interface to the physical world: devices that can
observe or control physical parameters of the environment.

• Communication - Device for sending and receiving information over a wireless

channel.

• Power supply - Batteries are necessary to provide energy. Recharging the battery
may obtain from solar cell

Controller:

The controller is the core and Central Processing Unit (CPU) of a wireless sensor node. It is
used to process all the relevant data, capable of executing arbitrary code.

• It collects data from the sensors

• Processes the data and decides when and where to send it

• Receives the data from other sensor nodes and decides on the actuator’s behavior.

• It has to execute various programs, ranging from time-critical signal processing and
communication protocols to application programs.

Microcontroller –General purpose processor

• Optimized for embedded applications and have Low power consumption

• Flexibility in connecting with other devices (like sensors)

 • They have in built memory and are freely programmable and hence very flexible.

• Reduce their power consumption by going into sleep states where only parts of the
controller are active

• Does not have Memory Management unit.

DSPs–optimized for signal processing tasks,

• Their architecture and their instruction set are used for processing large amounts of
vectorial data. In broadband wireless communication, DSPs are an appropriate and
successfully used platform.

• But in wireless sensor networks, the signal processing tasks related to the actual
sensing of data is also not overly complicated. Hence, these advantages of a DSP are
typically not required in a WSN node and they are usually not used.

FPGAs–may be good for testing

• An FPGA can be reprogrammed .It takes more time and energy

• It is not practical to reprogram an FPGA at the same frequency as a microcontroller

could change between different programs.

• An ASIC is a specialized processor and custom designed

• Flexibility is less but has better energy efficiency and performance.

• ASICs provide the functionality in hardware, resulting in potentially more costly

hardware development.

Microcontroller is the preferred solution as it is simple and has bigger flexibility

Some examples for microcontrollers are

Intel Strong ARM

• Fairly high-end processor as it is mostly geared toward handheld devices like PDAs.

• The SA-1100 model has a 32-bit Reduced Instruction Set Computer (RISC) core,
running at up to 206 MHz

Atmel AT mega

• 8-bit microcontroller, also intended for usage in embedded applications

• Equipped with relevant external interfaces for common peripherals.

Texas Instruments MSP 430

• Intended for embedded applications.

 • It runs a 16-bit RISC core at considerably lower clock frequencies (up to 4 MHz)

• Wide range of interconnection possibilities and an instruction set will be able to

handling of peripherals of different kinds.

• It features a varying amount of on-chip RAM (sizes are 2–10 kB),

• Several 12-bit analog/digital converters, and a real-time clock.

Memory:

• Random Access Memory (RAM)-Used to store intermediate sensor readings, and

packets from other nodes

• RAM is fast and loses its content if power supply is interrupted.

• Read-Only Memory (ROM)- Used to store Program codes

• Electrically Erasable Programmable Read-Only Memory (EEPROM) or flash

memory allows the data to be erased.

• Flash memory can also serve as intermediate storage of data in case RAM is
insufficient or when the power supply of RAM should be shut down for some time.

• Flash memory take long read and write delays and energy required is high.

SENSORS:

The actual interface to the physical world: devices that can observe or control physical
parameters of the environment

Sensors can be roughly categorized into three categories

1. Passive and omnidirectional sensors

2. Passive and narrow-beam sensors
3. Active sensors

Passive or omnidirectional sensors

• These sensors can measure a physical quantity at the point of the sensor node without
actually manipulating the environment by active probing – in this sense, they are
passive.
• Self-powered in the sense that they obtain the energy from the environment
• Energy is only needed to amplify their analog signal.
• There is no notion of “direction” involved in these measurements.
 • Typical examples for such sensors include thermometer, light sensors, vibration,
microphones, humidity, mechanical stress or tension in materials, chemical sensors
sensitive for given substances, smoke detectors, air pressure, and so on.

Passive and narrow-beam sensors

• These sensors are passive
• Have a well-defined notion of direction of measurement.
• Camera, which can “take measurements” in a given direction, but has to be rotated if
need be.

Active sensors
• This last group of sensors actively probes the environment, for example, a sonar or
radar sensor or some types of seismic sensors, which generate shock waves by small
explosions.
• It requires quite special attention.

Actuators
Actuators are just about as diverse as sensors, yet for the purposes of designing a WSN that
converts electrical signals into physical phenomenon. It controls

Communication Device
Choice of transmission medium:
• The communication device is used to exchange data between individual nodes.

• In wireless communication, the first choice to make is that of the transmission

medium – the usual choices include radio frequencies, optical communication and
ultrasound

• Other media like magnetic inductance are only used in very specific cases.
Radio Frequency (RF) - based communication is by far the most relevant one as it best fits
the requirements of most WSN applications.

Transceivers: For Communication, both transmitter and receiver are required in a sensor
node to convert a bit stream coming from a microcontroller and convert them to and from
radio waves.
For two tasks a combined device called transceiver is used. Transceiver structure has two
parts as Radio Frequency (RF) front end (Figure) and the baseband part.

A) The radio frequency front end performs analog signal processing in the actual radio
frequency Band.

B) The baseband processor performs all signal processing in the digital domain and
communicates with a sensor node’s processor or other digital circuitry.

Figure RF Front end

The RF front end performs analog signal processing in the actual radio frequency band, for
example in the 2.4 GHz Industrial, Scientific, and Medical (ISM) band.

The Power Amplifier (PA): It accepts upconverted signals from the IF or baseband part and
amplifies them for transmission over the antenna.

The Low Noise Amplifier (LNA): It amplifies incoming signals up to levels suitable for
further processing without significantly reducing the SNR.The range of powers of the
incoming signals may varies up to 100 dB .The LNA is active all the time and can consume a
significant fraction of the transceiver’s energy

Elements like local oscillators or voltage-controlled oscillators and mixers, are used for
frequency conversion from the RF spectrum to intermediate frequencies or to the baseband.
The incoming signal at RF frequencies fRF is multiplied in a mixer with a fixed frequency
signal from the local oscillator (frequency fLO). The resulting intermediate frequency signal
has frequency fLO − fRF. Depending on the RF front end architecture, other elements like
filters are also present.
Transceiver operational states
Many transceivers have four operational states
Transmit
• In the transmit state, the transmit part of the transceiver is active and the antenna
radiates energy.
Receive
• In the receive state the receive part is active.
Idle
• A transceiver that is ready to receive but is not currently receiving anything is said to
be in an idle state.
Sleep
In the sleep state, significant parts of the transceiver are switched off.
• IEEE 802.11 transceivers have different sleep states.
• These sleep states differ in the amount of circuitry switched off and in the associated
recovery times and startup energy
• For example, in a complete power down of the transceiver, the startup costs include a
complete initialization, whereas in “lighter” sleep modes, the clock driving certain
transceiver parts is shut down while configuration and operational state is
remembered

Transceiver tasks and characteristics

To select appropriate transceivers, a number of characteristics should be taken into account.
The most important ones are

Service to upper layer: A receiver has to offer certain services to the upper layers, most
notably to the Medium Access Control (MAC) layer. Sometimes, this service is packet
oriented; sometimes, a transceiver only provides a byte interface or even only a bit interface
to the microcontroller.

Power consumption and energy efficiency: The simplest interpretation of energy efficiency
is the energy required to transmit and receive a single bit. The transceivers should be
switchable between different states, for example, active and sleeping.

Carrier frequency and multiple channels: Transceivers are available for different carrier
frequencies; evidently, it must match application requirements and regulatory restrictions.

State change times and energy: A transceiver can operate in different modes: sending or
receiving, use different channels, or be in different power- safe states.

Data rates: Carrier frequency and used bandwidth together with modulation and coding
determine the gross data rate.

Modulations: The transceivers typically support one or several of on/off- keying, ASK, FSK,
or similar modulations.

Coding: Some transceivers allow various coding schemes to be selected.

Transmission power control: Some transceivers can directly provide control over the
transmission power to be used; some require some external circuitry for that purpose.
Usually, only a discrete number of power levels are available from which the actual
transmission power can be chosen. Maximum output power is usually determined by
regulations.
Noise figure: The noise figure NF of an element is defined as the ratio of the Signal-to-Noise
Ratio (SNR) ratio SNRI at the input of the element to the SNR ratio SNRO at the element’s
output:

NF= SNRI / SNRO

It describes the degradation of SNR due to the element’s operation and is typically given in
dB: NF dB= SNRI dB − SNRO dB.

Gain: The gain is the ratio of the output signal power to the input signal power and is
typically given in dB. Amplifiers with high gain are desirable to achieve good energy
efficiency.

Power efficiency: The efficiency of the radio front end is given as the ratio of the radiated
power to the overall power consumed by the front end; for a power amplifier, the efficiency
describes the ratio of the output signal’s power to the power consumed by the overall power
amplifier.

Receiver sensitivity: The receiver sensitivity (given in dBm) specifies the minimum signal
power at the receiver needed to achieve a prescribed Eb/N0 or a prescribed bit/packet error
rate.

Range: The range of a transmitter is clear. The range is considered in absence of

interference; it evidently depends on the maximum transmission power, on the antenna
characteristics.

Blocking performance: The blocking performance of a receiver is its achieved bit error rate
in the presence of an interferer.

Out of band emission: The inverse to adjacent channel suppression is the out of band
emission of a transmitter. To limit disturbance of other systems, or of the WSN itself in a
multichannel setup, the transmitter should produce as little as possible of transmission power
outside of its prescribed bandwidth, centered around the carrier frequency.

Carrier sense and RSSI: In many medium access control protocols, sensing whether the
wireless channel, the carrier, is busy (another node is transmitting) is a critical information.
The receiver has to be able to provide that information. The signal strength at which an
incoming data packet has been received can provide useful information a receiver has to
provide this information in the Received Signal Strength Indicator (RSSI).
 • Frequency stability: The frequency stability denotes the degree of variation
from nominal center frequencies when environmental conditions of oscillators
like temperature or pressure change.

• Voltage range: Transceivers should operate reliably over a range of supply

voltages. Otherwise, inefficient voltage stabilization circuitry is required.

Power Supply Unit of Sensor Nodes:

The batteries are necessary to provide energy. Sometimes, some form of recharging by
obtaining energy from the environment is available as well (e.g. solar cells). There are
essentially two aspects:

# Storing Energy

# Energy Scavenging

Storing Energy: Batteries

Traditional batteries: The power source of a sensor node is a battery, either non-
rechargeable (“primary batteries”) or, if an energy scavenging device is present on the node,
also rechargeable (“secondary batteries”).

Table Energy densities for various primary and secondary battery types

Upon these batteries the requirements are

Capacity: They should have high capacity at a small weight, small volume, and low price.
The main metric is energy per volume, J/cm3.

Capacity under load: They should withstand various usage patterns as a sensor node can
consume quite different levels of power over time and actually draw high current in certain
operation modes.

Self-discharge: Their self-discharge should be low. Zinc-air batteries, for example, have only
a very short lifetime (on the order of weeks).
Efficient recharging: Recharging should be efficient even at low and intermittently available
recharge power.

Relaxation:Self-recharging of an empty or almost empty battery when no current is drawn

from it, based on chemical diffusion processes within the cell is called Relaxation Effect.
Battery lifetime and usable capacity is considerably extended if this effect is leveraged.

DC–DC Conversion: Unfortunately, batteries alone are not sufficient as a direct power
source for a sensor node. One typical problem is the reduction of a battery’s voltage as its
capacity drops. A DC – DC converter can be used to overcome this problem by regulating the
voltage delivered to the node’s circuitry.

To ensure a constant voltage even though the battery’s supply voltage drops, the DC – DC
converter has to draw increasingly higher current from the battery when the battery is already
becoming weak, speeding up battery death. The DC – DC converter does consume energy for
its own operation, reducing overall efficiency.

Energy Scavenging
Depending on application, high capacity batteries that last for long times, that is, have only a
negligible self-discharge rate, and that can efficiently provide small amounts of current.
Ideally, a sensor node also has a device for energy scavenging, recharging the battery with
energy gathered from the environment – solar cells or vibration-based power generation are
conceivable options.
Photovoltaics: The well-known solar cells can be used to power sensor nodes. The available
power depends on whether nodes are used outdoors or indoors, and on time of day and
whether for outdoor usage. The resulting power is somewhere between 10 μW/cm2 indoors
and 15 mW/cm2 outdoors. Single cells achieve a fairly stable output voltage of about 0.6 V
which depends on the light intensity. Hence, solar cells are usually used to recharge
secondary batteries.

Temperature gradients: Differences in temperature can be directly converted to electrical

energy.

Vibrations: One almost pervasive form of mechanical energy is vibrations: walls or

windows in buildings are resonating with cars or trucks passing in the streets, machinery
often has low frequency vibrations. The energy depends on both amplitude and frequency of
the vibration and ranges from about 0.1 μW/cm3 up to 10, 000 μW/cm3 for some extreme
cases.

Pressure variations: Somewhat similar to vibrations, a variation of pressure can also be used
as a power source.

Flow of air/liquid: Another often-used power source is the flow of air or liquid in wind mills
or turbines. The challenge here is again the miniaturization, but some of the work on
millimeter scale MEMS gas turbines might be reusable.
Table : Comparison of Energy Sources

ENERGY CONSUMPTION OF SENSOR NODES:

• Energy efficiency is the key requirement to maximize sensor node lifetime. Sensor
nodes are typically powered by a battery source that has finite lifetime.

• Hence, the energy consumption of a sensor node must be tightly controlled. The main
consumers of energy are the controller, the radio front ends, the memory, and type of
the sensors.

• One method to reduce power consumption of these components is designing low-

power chips, it is the best starting point for an energy-efficient sensor node. But any
advantages gained by such designs can easily be squandered/ wasted when the
components are improperly operated.

• Second method for energy efficiency in wireless sensor node is reduced functionality
by using multiple states of operation with reduced energy consumption. These modes
can be introduced for all components of a sensor node, in particular, for controller,
radio front end, memory, and sensors.

Microcontroller Energy Consumption

• For a controller, typical states are “active”, “idle”, and “sleep”. A radio modem could
turn transmitter, receiver, or both on or off.
• Sensors and memory could also be turned on or off
 • At time t1, the microcontroller is to be put into sleep mode should be taken to reduce
power consumption from Pactive to Psleep.

• But if it remains active and the next event occurs at time tevent, then a total energy is
Eactive=Pactive (tevent − t1).

• On the other hand, requires a time τdown until sleep mode has been reached. Let the
average power consumption during this phase is (Pactive + Psleep)/2. Then, Psleep is
consumed until tevent.
• The energy saving is given by
• Esaved = (tevent − t1)Pactive − (τdown (Pactive + Psleep)/2 +(tevent − t1 − τdown )Psleep)
• Once the event to be processed occurs, however, an additional overhead of
Eoverhead = τUp (Pactive + Psleep)/2

• Switching to a sleep mode is only beneficial if Eoverhead < Esaved or, equivalently,
if the time to the next event is sufficiently large:

Examples:

1. Intel StrongARM : The Intel StrongARM provides three sleep modes:

In normal mode, all parts of the processor are fully powered. Power consumption is up to
400 mW.

In idle mode, clocks to the CPU are stopped; clocks that pertain to peripherals are active.
Any interrupt will cause return to normal mode. Power consumption is up to 100 mW.

In sleep mode, only the real-time clock remains active. Wakeup occurs after a timer interrupt
and takes up to 160 ms. Power consumption is up to 50 μW.
2. Texas Instruments MSP 430 : The MSP430 family features a wider range of operation
modes: One fully operational mode, which consumes about 1.2 mW (all power values given
at 1 MHz and 3 V). There are four sleep modes in total. The deepest sleep mode, LPM4, only
consumes 0.3 μW, but the controller is only woken up by external interrupts in this mode. In
the next higher mode, LPM3, a clock is also till running, which can be used for scheduled
wake ups, and still consumes only about 6 μW.

3. Atmel ATmega : The Atmel ATmega 128L has six different modes of power
consumption, which are in principle similar to the MSP 430 but differ in some details. Its
power consumption varies between 6 mW and 15 mW in idle and active modes and is about
75 μW in power-down modes.

Memory Energy Consumption

• The most relevant kinds of memory are on-chip memory and FLASH memory. Off-
chip RAM is rarely used. In fact, the power needed to drive on-chip memory is
usually included in the power consumption numbers given for the controllers.

• Hence, the most relevant part is FLASH memory. In fact, the construction and usage
of FLASH memory can heavily influence node lifetime. The relevant metrics are the
read and write times and energy consumption. Read times and read energy
consumption tend to be quite similar between different types of FLASH memory.
Energy consumption necessary for reading and writing to the Flash memory is used
on the Mica nodes. Hence, writing to FLASH memory can be a time- and energy-
consuming task that is best avoided if somehow possible.

Radio Transceivers Energy Consumption

• A radio transceiver has essentially two tasks: transmitting and receiving data between
a pair of nodes. Similar to microcontrollers, radio transceivers can operate in different
modes, the simplest ones are being turned on or turned off.

• To accommodate the necessary low total energy consumption, the transceivers should
be turned off most of the time and only be activated when necessary – they work at a
low duty cycle.

• The energy consumed by a transmitter is due to two sources one part is due to RF
signal generation, which mostly depends on chosen modulation and target distance.
Second part is due to electronic components necessary for frequency synthesis,
frequency conversion, filters, and so on.

• The transmitted power is generated by the amplifier of a transmitter. Its own power
consumption Pamp depends on its architecture Pamp = αamp + βampPtx, where αamp
and βamp are constants depending on process technology and amplifier architecture.
• This model implies that the amplifier’s efficiency η =Ptx/Pamp is best at maximum
output power
 • The energy to transmit a packet n-bits long (including all headers) then depends on
how long it takes to send the packet, determined by the nominal bit rate R and the
coding rate Rcode, and on the total consumed power during transmission.

• Similar to the transmitter, the receiver can be either turned off or turned on. While
being turned on, it can either actively receive a packet or can be idle, observing the
channel and ready to receive. Evidently, the power consumption while it is turned off
is negligible.

• Even the difference between idling and actually receiving is very small and can, for
most purposes, be assumed to be zero. To elucidate, the energy Ercvd required to
receive a packet has a startup component Tstart Pstart similar to the transmission case
when the receiver had been turned off (startup times are considered equal for
transmission and receiving here); it also has a component that is proportional to the
packet time n / RRcode.

• During this time of actual reception, receiver circuitry has to be powered up, requiring
a (more or less constant) power of PrxElec.

Power Consumption of Sensor and Actuators

• Providing any guidelines about the power consumption of the actual sensors and
actuators is impossible because of the wide variety of these devices.

• For example, passive light or temperature sensors – the power consumption can
possibly be ignored in comparison to other devices on a wireless node. For others,
active devices like sonar, power consumption can be quite considerable in the
dimensioning of power sources on the sensor node, not to overstress batteries.
• In addition, the sampling rate evidently is quite important. Not only does more
frequent sampling require more energy for the sensors as such but also the data has to
processed and, possibly,communicated somewhere.

SENSOR NETWORK SCENARIOS:

Types of sources and sinks

A source is any entity in the network that can provide information, that is, typically a sensor
node

• It could also be an actuator node that provides feedback about an operation.

• A sink is the entity where information is required.

 • There are essentially three options for a sink:

▫ It could belong to the sensor network

▫ Another sensor/actuator node

▫ It could be an entity outside this network.

Three Types of Sink:

• For the second case, the sink could be an actual device - a handheld or PDA used to
interact with the sensor network.

• For the third case -It could also be gateway to another larger network such as the
Internet where the actual request for the information comes from some node.

SINGLE-HOP VERSUS MULTIHOP NETWORKS:

Direct communication between source and sink is not always possible in WSNs.Why?

➢ Power limitation of radio communication follows the limited distance

➢ Cannot cover a lot of ground (e.g. in environmental or agriculture applications)

➢ Difficult to operate in radio environments with strong attenuation (e.g. in buildings).

To overcome such limited distances, the data packets take multi hops from the source to the
sink.
 • Multihop is a solution for obstacles and large distance problem

• Source send packets to the intermediate nodes and the intermediate nodes send the
packets to the destination.

• Store and forward multihop network

• Multihopping also improve the energy efficiency of communication.

• The attenuation of radio signals is at least quadratic in most environments

• It consumes less energy to use relays instead of direct communication

• When targeting for a constant SNR at all receivers , the radiated energy required for
direct communication over a distance d is c *d^α (c some constant, α ≥ 2 the path loss
coefficient)

• Using a relay at distance d/2 reduces this energy to 2c*(d/2)^α.

• But this calculation considers only the radiated energy, not the actually consumed
energy

• Energy is actually wasted if intermediate relays are used for short distances d.

• Only for large d does the radiated energy dominate the fixed energy costs consumed
in transmitter and receiver electronics

Three types of mobility:

Wireless communication is able to support mobile participants.

In wireless sensor networks, mobility are in three main forms:

Node mobility Sink mobility Event mobility

Node mobility

• The wireless sensor nodes themselves can be mobile.

• The mobility is highly application dependent.

In examples like environmental control-No node mobility

Sensor nodes attached to cattle- Node mobility is there

• The network has to reorganize itself frequently enough to be able to function

correctly.

• Trade-offs between the speed of node movement and the energy required to maintain
a desired level of functionality in the network

Sink mobility

• The information sinks can be mobile.

• The mobility of an information sink is not part of the sensor network

• For example, a human user requested information via a PDA while walking in an
intelligent building.

In a simple case, such a requester can interact with the WSN at one point and

complete its interactions before moving on.

• In many cases, consecutive interactions can be treated as separate, unrelated requests.

• Whether the requester is allowed interactions with any node or only with specific
nodes is a design choice for the appropriate protocol layers.

• The network with the assistance of the mobile requester should make the requested
data reaches the requester despite its movements

•
Event mobility
 • In applications like event detection and in particular in tracking applications, the
cause of the events or the objects to be tracked can be mobile.

• The observed event is covered by a sufficient number of sensors at all time.

• Hence, sensors will wake up around the object, engaged in higher activity to observe
the present object, and then go back to sleep.

• As the event source moves through the network, it is accompanied by an area of

activity within the network – this has been called the frisbee model

• The task is to detect a moving elephant and to observe it as it moves around.

• Nodes that do not actively detect anything are intended to switch to lower sleep
states

• Nodes become active only when elephant is near by and they will convey information
from the zone of activity to some remote sink

Event mobility
Dashed line -Elephant’s trajectory
Shaded ellipse- the activity area following the elephant

OPTIMIZATION GOALS AND FIGURES OF MERIT :

For all WSN scenarios and application types have to face the challenges such as
• How to optimize a network and How to compare these solutions?
• How to decide which approach is better?
• How to turn relatively inaccurate optimization goals into measurable figures of merit?
For all the above questions the general answer is obtained from
1. Quality of service
2. Energy efficiency
3. Scalability
4. Robustness
1.Quality of Service:

• WSNs differ from other conventional communication networks mainly in the type of
service they offer.
• High-level QoS attributes in WSN are highly depend on the application.
• Some generic possibilities are:
Event detection/reporting probability
Event classification error
Event detection delay Missing reports
Approximation accuracy
Tracking accuracy

Event detection/reporting probability: The probability that an event that actually occurred
is not detected or not reported to an information sink that is interested in such an event For
example, not reporting a fire alarm to a surveillance station would be a severe shortcoming.

Event classification error

• If events are not only to be detected but also to be classified, the error in
classification must be small.
Event detection delay
• The delay between detecting an event and reporting it to the interested sinks should
be small
Missing reports
• In applications that require periodic reporting, the probability of undelivered reports
should be small.

Approximation accuracy:
For function approximation applications, the average/maximum absolute or relative error
with respect to the actual function should be considered.
Tracking accuracy
• Tracking applications must not miss an object to be tracked, the reported position
should be as close to the real position as possible, and the error should be small.

2.Energy efficiency:
• Energy is a precious resource in WSN and hence it is an optimization goal.
• If amount of energy increases, most of the QoS metrics also increases
•
• Energy per correctly received bit: How much energy is spent on average to
transport one bit of information (payload) from the transmitter to the receiver.

• Energy per reported (unique) event: What is the average energy spent to report one
event.

• Delay/energy trade-offs: “urgent” events increases energy investment for a speedy

reporting events. Here, the trade-off between delay and energy overhead is interesting.
 • Network lifetime: The time for which the network is operational.

• Time to first node death- Time taken by the first node in the network to run out of
energy or fail and stop operating.

• Network half-life – Time taken by 50% of the nodes to run out of energy and
stopped operating

• Time to partition – Time taken by the network to be disconnected and partitioned

into two or more

• Time to loss of coverage: The time when for the first time any spot in the
deployment region is no longer covered by any node’s observations.

• Time to failure of first event notification: A network partition can be seen as

irrelevant if the unreachable part of the network does not want to report any events in
the first place

• The longer these times are, the better does a network perform.

3.Scalability:
• The ability to maintain performance characteristics irrespective of the size of the
network is referred to as scalability. With WSN potentially consisting of thousands of
nodes, scalability is an obviously essential requirement.
• The need for extreme scalability has direct consequences for the protocol design.
• Architectures and protocols should implement appropriate scalability support.
• Applications with a few dozen nodes might admit more efficient solutions than
applications with thousands of nodes
4.Robustness:
• Wireless sensor networks should also exhibit an appropriate robustness.
• They should not fail just because a limited number of nodes run out of energy, or
because their environment changes and severs existing radio links between two nodes
• If possible, these failures have to be compensated by finding other routes.
• Evaluation of robustness is difficult in practice and depends mostly on failure models
for both nodes and communication links.