Wireless sensor network survey

1. Wireless sensor network survey
Author: Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal
Reported by Jiang

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Introduction
•
Subject: wireless sensor network (WSN)
•
WSN consists of spatially distributed
autonomous sensors to monitor physical or
environmental conditions, such as
temperature, sound, pressure, etc. and to
cooperatively pass their data through the
network to a main location.
What?

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Overall image
A typically WSN consists of generic and gateway nodes.

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Typically WSN
•
A WSN typically has little or no infrastructure.
There are two types of WSNs.

Structured WSN

Unstructured WSN

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Structured WSN
•
Deployed in a pre-planned manner
•
Fewer nodes
•
Lower network maintenance
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Lower cost
•
No uncovered regions

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Unstructured WSN
•
Densely deployed (many node)
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Randomly Deployed
•
Can have uncovered regions
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Left unattended to perform the task
•
Maintenance is difficult
a . managing connectivity
b. detecting failures

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generic nodes
gateway nodes

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Requirement
WSN
military target tracking
hazardous environment
exploration
natural disaster relief
surveillance
biomedical health
monitoring
seismic
sensing

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Why we select WSN ?
Not traditional networks.
•
Power and environment constraints
determine us to design a lower power,
feasible, and smart network.
•
Sensors that are smaller, cheaper, and
intelligent.

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About this paper
•
Goal: present a comprehensive review of the
recent literature.
a . An overview of the key issues in a WSN
b. Compare different types of sensor
networks
c. Applications on WSN
d. Internal sensor system
e . Network services
f. Communication protocol

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Key issues
•
Energy constraint
•
Quality of service (QoS)
Each sensor node is an individual system.
Development should satisfy current
requirement.
Self-organizing
Consume less power
Total number and
placement
Address network dynamics
Optimize communication and
be energy efficiency

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Types of sensor networks
1. terrestrial WSN
•
Ad Hoc (unstructured)
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Preplanned (structured)
1. underground WSN
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Preplanned, with additional sink nodes to relay data.
•
more expensive equipment, deployment,
maintenance
1. underwater WSN
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fewer sensor nodes( sparse deployment)
•
more expensive than terrestrial
•
acoustic wave communication
–
Limited bandwidth
–
long propagation delay
–
signal fading

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Types of sensor networks(cont.)
4. multi-media WSN
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sensor nodes equipped with cameras and
microphones
•
pre-planned to guarantee coverage
•
High bandwidth/low energy, QoS, filtering, data
processing and compressing techniques
4. mobile WSN
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ability to reposition and organize itself in the network
•
Start with Initial deployment and spread out to gather
information
•
deployment, localization, self-organization, navigation
and control, coverage, energy, maintenance, data

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WSN applications

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Example: CenWits
• Berkeley Mica2 sensor mote
• GPS receivers
• radio frequencies (RF)-based
sensors
• storage and processing devices

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Internal sensor system

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Internal sensor system
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sensor platform
–
radio components
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processors
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Storage
–
sensors (multiple)
•
OS
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OS must support these sensor platforms.
It’s hard to design a general platform to be applied to all
applications due to requirements vary in terms computation,
storage and user interface.

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Internal sensor system
Standards
•
IEEE 802.15.4, ZigBee
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WirelessHART
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ISA100.11
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IETF 6LoWPAN
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IEEE 802.15.3
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Wibree

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Internal sensor system
Standard example: ZigBee
•
IEEE 802.15.4:
–
standard for low rate wireless
personal area networks (LR-WPAN)
–
low cost deployment, low
complexity, power consumption
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topology :star and peer-to-
peer
–
MAC layer: CSMA-CA
mechanism
•
ZigBee
–
simple, low cost, and low
power
–
embedded applications
–
can form mesh networks

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Internal sensor system
Storage
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problems
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storage space is limited
–
Communication is expensive
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Solutions
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Aggregation and compression
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query-and-collect (selective gathering)
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a storage model to satisfy storage constraints and query
requirements

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Internal sensor system
Testbeds
•
Provides researchers a way to test their protocols,
algorithms, network issues and applications in real
world setting
•
Controlled environment to deploy, configure, run,
and monitoring of sensor remotely

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Internal sensor system
Testbeds example: Orbit
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a two-dimensional grid of 400 802.11 radio nodes.
•
dynamically interconnected into specified topologies
with reproducible wireless channel models.

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Internal sensor system
Diagnostics and debugging support
•
Measure and monitor the sensor node
performance of the overall network
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To guarantee the success of the sensor
network in the real environment

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Network services
a . Localization
b. Synchronization
c. Coverage
d. Compression and
aggregation
e . Security

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Network services
Localization
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Problem:
–
determining the node’s location (position)
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Solutions:
–
global positioning system (GPS)
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Simple
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Expensive
•
outdoor
–
beacon (or anchor) nodes
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does not scale well in large networks
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problems may arise due to environmental conditions
–
proximity-based
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Make use of neighbor nodes to determine their position
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then act as beacons for other nodes
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Other solutions

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Network services
Synchronization
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Time synchronization is important for
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routing
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power conservation
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Lifetime
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Cooperation
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Scheduling

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Network services
Coverage
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Is important in evaluating effectiveness
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Degree of coverage is application dependent
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Impacts on energy conservation
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Techniques:
–
selecting minimal set of active nodes to be
awake to maintain coverage
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sensor deployment strategies

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Network services
Compression and aggregation
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Both of them
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reduce communication cost
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increase reliability of data transfer
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Data-compression
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compressing data before transmission to base
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Decompression occurs at the base station
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no information should be lost
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data aggregation
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data is collected from multiple sensors
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combined together to transmit to base station
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Is used in cluster base architectures

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Network services
Security
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Constraints in incorporating security into a
WSN
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limitations in storage
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limitations in communication
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limitations in computation
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limitations in processing capabilities

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Network services
Open research issues
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localization
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efficient algorithms
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minimum energy
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minimum cost
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minimum localization errors
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Coverage: optimizing for better energy conservation
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time synchronization: minimizing uncertainty errors over long periods of
time and dealing with precision
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compression and aggregation: Development of various scheme
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event-based data collection
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continuous data collection
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Secure monitoring: protocols have to monitor, detect, and respond to
attacks
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It has done for network and data-link layer (can be improved)
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Should be done for different layers of the protocol stack
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Cross-layer secure monitoring is another research area

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Communication protocol
a . Transport layer
b. Network layer
c. Data-link layer
d. Physical layer

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Communication protocol
Transport layer
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Packet loss
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may be due to
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bad radio communication,
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congestion,
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packet collision,
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memory full,
•
node failures
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Detection and recovering
•
Improve throughput
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Energy expenditure

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Communication protocol
Transport layer
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Congestion control/packet recovery
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hop-by-hop
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intermediate cache
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more energy efficient (shorter
retransmission)
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higher reliability
–
end-to-end
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source caches the packet
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Variable reliability

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Communication protocol
Transport layer(Open research issues)
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cross-layer optimization
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selecting better paths for retransmission
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getting error reports from the link layer
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Fairness
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assign packets with priority
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frequently-changing topology
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Congestion control with active queue
management

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Communication protocol
Network layer
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Important:
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energy efficiency
–
traffic flows
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Routing protocols
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location-based: considers node location to route
data
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cluster-based: employs cluster heads to do data
aggregation and relay to base station

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Communication protocol
Network layer (Open research issues)
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Future research issues should address
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Security
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Experimental studies regarding security applied to
different routing protocols in WSNs should be examined
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QoS
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guarantees end-to-end delay and energy efficient routing
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node mobility
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handle frequent topology changes and reliable delivery

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Communication protocol
Data-link layer (Open research issues)
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system performance optimization
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Cross-layer optimization
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Cross-layer interaction can
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reduce packet overhead on each layer
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reduce energy consumption
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Interaction with the MAC layer provide
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congestion control information
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enhance route selection
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Comparing performance of existing protocols of static
network in a mobile network
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improve communication reliability and energy efficiency

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Communication protocol
Physical layer
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Minimizing the energy consumption
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Optimizing of circuitry energy
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reduction of wakeup and startup times
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Optimizing of transmission energy
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Modulation schemes
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Future work
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new innovations in low power radio design with emerging
technologies
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exploring ultra-wideband techniques as an alternative for
communication
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creating simple modulation schemes to reduce synchronization and
transmission power
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building more energy-efficient protocols and algorithms

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Communication protocol
Cross-layer interactions (Open research issues)
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Collaboration between all the layers to
achieve higher
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energy saving
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network performance
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network lifetime

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Thanks!
That’s all for today.