wireless sensor network unit-2

1. WIRELESS SENSOR NETWORKS
Prepared By: Dr. Nagarathna and Deepika
Dept. of CS & E
PESCE, Mandya
1

2. BASIC WIRELESS SENSOR
TECHNOLOGY
2

3. SENSOR NODE TECHNOLOGY
 A WSN node consists of a group of dispersed
sensors(motes) that have the responsibility of
covering a geographical area(sensor field) in terms
of some measured parameter(measurand).
 A sensor supports a point –to-point link in which
reader end is attached to a wireline network.
 Sensor nodes have wireless communication
capabilities and some logic signal processing,
topology management and transmission handling.
3

4. SENSOR NODES
4
Sensor node, Wireless node (WN), Smart Dust, mote (COTS - commercial off-
the-shelf)

5. BASIC FUNCTIONALITY OF A WN
Depends on the application, typical basic functionality
1. Determine the value of a parameter at a given location
EX:
 Temperature
 Atmospheric pressure
 Sunlight
 Humidity
 Different types of sensors with
 Different sampling rate
 Range of allowed values
(Cont
d---)
5

6. BASIC FUNCTIONALITY OF A WN
2. Detect the occurrence of events of interest and estimate
the parameters of the events
Ex:
Traffic-oriented WSN
 Detect a vehicle moving through an intersection and
estimate
 Speed
 Direction of the vehicle
6(Contd---)

7. BASIC FUNCTIONALITY OF A WN
3. Classify an object that has been detected
Ex:
Classify vehicle in a traffic as
 Car
 Minivan
 Light truck
 Bus
7(Contd--
-)

8. BASIC FUNCTIONALITY OF A WN
4. Track an object
Ex:
In a military WSN
 Track an enemy tank as it moves through the
geographic area covered by the network
8

9. SENSOR CLASSIFICATION SCHEMES
Sensors can be classified, among others, according to one of the following criteria
 Power supply requirements
Passive and active
 Nature of the output signal
Digital and analog
 Measurement operational mode
Deflection and null modes
 Input/output dynamic relationships
Zero, first, second order, etc.
 Measurand
Mechanical, thermal, magnetic, radiant, chemical
 Physical measurement variable
Resistance, inductance, capacitance, etc
9

10. SENSING PRINCIPLES
Mechanical
Chemical
Thermal
Electrical
Magnetic
Biological
Fluidic
Optical
Ultrasonic
More & More 10

11. TECHNOLOGY FOR SENSING AND CONTROL
• Electric and Magnetic field sensors
• Radio-wave frequency sensors
• Optical
• Electro optic
• Infrared sensors
• Radars
• Lasers
• Location and navigation sensors
• Seismic and Pressure-wave sensors
• Environmental parameter sensors (e.g., wind, humidity, heat)
• Biochemical
• National Security–oriented sensors.
11

12. SENSOR PARAMETERS (MEASURANDS)
Typical sensor parameters (measurands) include
1. Physical measurement
Ex:
 light and ultraviolet intensity (photo resistor)
 Humidity, temperature (thermistor)
 sound and acoustics
 shock wave, seismic, physical pressure
 video and image
 Location (GPS)
12
(Contd---)

13. SENSOR PARAMETERS (MEASURANDS)
2. Chemical and biological measurements
Ex:
 Presence or Concentration of a substance or
agent at specified concentration levels
(More than 50 biological agents of interest)
13
(Contd--
-)

14. SENSOR PARAMETERS (MEASURANDS)
3. Event measurement
Ex:
Determination of the occurrence of Human-made or
natural events
 Cyber-level events
 Tracking of internal and external events
14

15. NODE FUNCTIONALITY
 Digital signal processing (e.g., FFT/DCT(time or space)),
 Compression
 Forward error correction
 Encryption
 Control and actuation
 Clustering and in-network computation
 Communication
 Routing and forwarding
 Connectivity management
15

16. HARDWARE COMPONENTS
 Sensing and actuation unit (single element or
array)
 Processing unit
 Communication unit
 Power unit
 Application-dependent units
16

17. HARDWARE COMPONENTS OF WN’S
17

18. FOUR HARDWARE SUBSYSTEMS
1. Power
Energy infrastructure to support operation from a few hours to months or years
2. Computational Logic and Storage
To handle
 Onboard data processing and manipulation
 Transient and short-term storage
 Encryption
 Forward error correction (FEC)
 Digital modulation and digital transmission
Computational requirements ranging from an 8-bit microcontroller to a 64-bit
microprocessor
Storage requirements range from 0.01 to 100 gigabytes (GB).
(Contd….)
18

19. FOUR HARDWARE SUBSYSTEMS
3. Sensor transducer(s)
The interface between the environment and the WN is the sensor
4. Communication
WNs must have the ability to communicate
 C1WSN
 Mesh-based systems with multihop radio connectivity among or between
WNs
 Dynamic routing in both the wireless and wire line portions
 C2WSN
 Point-to-point or multipoint-to-point with single-hop radio connectivity to
WNs
 Static routing over the wireless network with only one route
(Contd
….) 19

20. FOUR HARDWARE SUBSYSTEMS
 Distances range from a few meters to a few kilometers
 lower-layer communication protocols tend to be of the
 IEEE 802.11
 IEEE 802.15
 IEEE 802.16
 Throughput ranges from 10 to 256 kbps in most applications
 Video-based application may require more bandwidth
20

21. SOFTWARE SUBSYSTEMS
Sensors typically have five basic software subsystems:
 Operating system
 Sensor drivers
 Communication processors
 Communication drivers
 Data processing mini-apps
21

22. SOFTWARE SUBSYSTEMS
22

23. OPERATING SYSTEM (OS) MICROCODE
 Also called Middleware
 Board-common microcode
 Used by all high-level node-resident software modules to support various functions
 Purpose is to shield the software from the machine-level functionality of the
microprocessor
 Desirable to have open-source operating systems designed for WSNs
Advantage
 Rapid implementation
 Minimizing code size
 Example: TinyOS
23

24. SENSOR DRIVERS
(Sensors may possibly be of the modular/plug-in type)
 Manage basic functions of the sensor transceivers
 Appropriate configuration and settings must be
uploaded into the sensor
24

25. COMMUNICATION PROCESSORS
 Manages the communication functions
 Routing
 Packet buffering and forwarding
 Topology maintenance
 Medium access control (e.g., contention mechanisms, direct-
sequence spread-spectrum (chipping code): (resist interference,
recovery from damaged )
 Encryption
 Forward Error Correction 25

26. COMMUNICATION DRIVERS
 Software modules manage and deals with Encoding
and the physical layer
 Software modules manage
Radio channel transmission link
Clocking and synchronization
Signal encoding
Bit recovery
Bit counting
Signal levels
Modulation.
26

27. DATA PROCESSING MINI-APPS
Basic applications that are supported at the node
level for in-network processing
 Numerical
 Data-processing
 Signal value storage and manipulations
27

28. 28

29. BASIC TAXONOMY OF SENSOR NODES
29

30. BASIC TAXONOMY OF SENSOR NODES
30

31. REDUCED-COMPLEXITY TAXONOMY OF
SENSOR NODES
31

32. WN OPERATING ENVIRONMENT
 Sensor nodes have to deal with the following
resource constraints
Power consumption
Communication
Computation
Uncertainty in measured parameters
32

33. Power consumption
 WNs have a limited supply of operating energy
 Energy conservation is a key system design
consideration
33

34. COMMUNICATION
 The wireless network has limited bandwidth
 Networks may be forced to utilize a noisy channel
 Communication channel may be relegated to an
unprotected frequency band
 The implications are
 Limited reliability
 Poor quality of service (e.g., high latency, high variance, high frame loss)
 Security exposure (e.g., denial of service, jamming, interference, high bit-
error rates). 34

35. COMPUTATION
 WNs have limited computing power and memory
resources
 Restrictions on types of data-processing algorithms
 Limits the scope and volume of intermediate results that can be stored
Research aims to
 Develop a distributed data management layer
 Scales with the growth of sensor interconnectivity
 Computational power on the sensors
35

36. COMPUTATION
Goal
 To deploy mechanisms directly on the
sensor nodes (autonomous)
 Without centralizing data or computation.
36

37. UNCERTAINTY IN MEASURED PARAMETERS
 Signals that have been detected or collected may be
with uncertainty
 Commingled with noise
 Interference from the environment
 Node malfunction could collect and/or forward inaccurate data.
 Node placement may impair operation and bias individual
readings.
37

38. DESIGN CONSTRAINTS(WSN AND WN)
Factors to consider during design of WN and WSN
 Deployed in a dense manner - communication complexity
 Rapid deployment - Environment is expected to be highly
dynamic
 WNs may be prone to failure- Sensing systems that are
long-lived and environmentally resilient
 Communication circuitry and antennas use most of the
energy. 38

39. DESIGN CONSTRAINTS(WSN AND WN)
 The topology may change very frequently
 Communication links may be expensive
 Bandwidth may be limited
 Power availability at the sensor may be limited and/or
expensive
 No global addresses because of
 Large number of sensors
 Overhead needed to support such global addresses
39

40. DESIGN CONSTRAINTS(WSN AND WN)
 WNs require special routing and data dissemination mechanisms
 WNs often require in-network processing
 Data aggregation,
 Data fusion
 Data analysis.
Interest in
 Database management,
 Querying mechanisms
 Data storage and warehousing.
 High-speed connectivity to processing centers for
 Decision
 Responsive action
Arrays of ultralow-power wireless nodes may be incorporated in
reconfigurable networks
40

41. DESIGN CONSTRAINTS(WSN AND WN)
 Design Constraints or Requirements for WSNs and
WNs
 Collaborative data processing
 Constrained energy use
 Large topology support
 Querying capabilities
 Self-organization
41

42. WN TRENDS
 To achieve
 Wide-scale deployment
 To decrease the size, cost, and power consumption
 Intelligence of the WNs must increase
 Sensor systems must incorporate advances in technologies
 Nanofabrication
 Bio systems
 Distributed networks
 Ubiquitous computing
 Broadband wireless communications
 Information and decision systems
Contd
… 42

43. WN TRENDS
 Evolving requirements for new WSNs and WNs include :
1 . The ability to respond to
Toxic chemicals
Explosives
Biological agents
2. Enhanced
 Sensitivity
 Selectivity
 Speed
 Robustness
 Fewer false alarms
Cont
d..43

44. WN TRENDS
3. Ability to function autonomously in
 Unusual
 Extreme
 Complex environments
 Addressed by the design and synthesis of
functionalized receptors and materials
resulting in next-generation devices
Cont
d..44

45. WN TRENDS
 Miniaturization, Manufacturability and Cost are also critical
issues
 Integration of
 sensors, processors, energy sources and communications
network interface on a chip
 Information extraction involve
 Detection of events or objects of interest
 Estimation of key parameters
 Human-in-the-loop or closed-loop adaptive feedback (Human
interaction/ prediction)
45

46. GOALS
To Develop
 Low-cost (i.e., <50 cents) transceivers for ubiquitous wireless data acquisition
With
 Minimal energy dissipation (<5 nJ/ bit)
for an
 Energy-limited source and minimize power (<100 mW for a power-limited source,
enabling energy scavenging)
 Using strategies like
 Self configuring networks
 fluid trade-off between communication and computation
 System-on-a-chip (SOC) approach
 Aggressive low-energy architectures and circuits
46

47. WN TRENDS
 Standardization is important.
 The application interface for WSNs should be an
 Abstraction offered to any sensor network application
 Supported by any sensor network platform
 Research and engineering activity seeks to advance fundamental knowledge in
new sensor technologies:
 Toxic chemicals
 Explosives
 Biological agents
 Sensor networking systems in a distributed environment
 Integration of sensors into commercial systems
 Interpretation and use of sensor data in decision-making processes
47

48. RESEARCH EFFORTS SPONSORED BY U.S.
GOVERNMENT AGENCIES
 Designs, materials, and concepts for new sensors and
sensing systems
 Arrayed sensor networks and networking
 Interpretation decision and action base on sensor data
48

49. New sensors and sensing systems
 Design of solid and liquid surfaces with molecular recognition,
 Long lifetime, and re generability of the sensing site
 Biomimetic sensors : hybrids consisting of proteins, enzyme fragments
and components,
 Sensors for toxic agents (biological, chemical, radiation)
 Sensors for operation in harsh environments
 Chip-based systems incorporating multiple sensors
 Computation, actuation and wireless interfaces
 Sensor power sources
 New modeling and simulation tools
 New techniques for on-sensor self-calibration and self-test
 Enhanced specificity to maximize accuracy and minimize false alarms
 New methods for sensor
 Fabrication
 Manufacture
 Encapsulation.
49

50. Arrayed sensor networks and
networking
 Enabling networking technologies for distributed wireless and
wired sensor networks
 Scalable and robust architectures
 Design
 Automated tasking
 Querying techniques
 Adaptive management and control of sensor nodes
 Security and authentication for resource-constrained sensor
networks
 Mobile sensor networks
 Scalable reconfigurability and self-organization 50

51. DECISION AND ACTION BASE ON SENSOR
DATA
 Decision theory for intelligent use of sensed information
 Detection and identification of false alarms
 Feedback theory
 Statistical algorithms,
 Mathematical hybrid system tools for monitoring distributed networks of
large arrays of sensors and actuators
 Handheld diagnostic kits
 Pattern recognition and state estimation
 Biomedical health monitoring, diagnostic, and therapeutic systems
 Image-guided surgery
 Health monitoring systems for civil structures
 Crisis management sensor systems
 Surveillance technology
 Robotics
 Mobile sensors
 Tracking and monitoring of mobile units
51