Wireless sensor
networks: a survey
周紹恩
指導教授:柯開維
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Outline
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Introduction
Sensor networks applications
Factors influencing sensor network design
Sensor networks communication architecture
Routing protocols
Conclusion & Future work
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Introduction
• A sensor network is composed of a large number of sensor
nodes
• densely deployed either inside the phenomenon or very close to it
• Sensor networks represent a significant improvement
• Sensors can be positioned far from the actual phenomenon
• Several sensors that perform only sensing can be deployed
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What’s different with Ad hoc?
• Sensor nodes are densely deployed
• Sensor nodes are prone to failures
• The number of sensor nodes in a sensor network can be
several orders of magnitude higher than the nodes in an ad
hoc network
• The topology of a sensor network changes very frequently
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Sensor networks applications
• Sensor networks may consist of many different types of
sensors such as:
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Temperature
Pressure
Noise levels
Seismic
• The concept of micro-sensing and wireless connection of
these nodes promise many new application areas
• Health
• Military
• Home and other commercial areas
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Military applications
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Monitoring friendly forces, equipment and ammunition
Battlefield surveillance
Reconnaissance of opposing forces and terrain
Targeting
Battle damage assessment
Nuclear, biological and chemical attack detection and
reconnaissance
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Factors influencing
• Fault tolerance is the ability to sustain sensor network
functionalities without any interruption due to sensor node
failures
• Physical damage
• Environmental interference
• Lack of power
• Note that protocols and algorithms may be designed to
address the level of fault tolerance required by the sensor
networks
• deployed in a house
• deployed in a battlefield
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Scalability
• the number of nodes in a region can be used to indicate the
node density
• The node density depends on the application in which the
sensor nodes are deployed
• For machine diagnosis application, the node density is around
300 sensor nodes in a 5x5 𝑚2 region
• vehicle tracking application is around 10 sensor nodes per region
• The density will be extremely high when a person normally
containing hundreds of sensor nodes
• eye glasses, clothing, shoes, watch, jewelry, and human body…..
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Production costs
• the cost of a single node is very important
• Since the sensor networks consist of a large number of sensor
nodes
• As a result, the cost of each sensor node has to be kept low
• Bluetooth radio system to be less than 10$
• PicoNode is targeted to be less than 1$
• The cost of a sensor node should be much less than 1$ in
order for the sensor network
• Note that a sensor node also has some additional units such as
sensing and processing units
• As a result, the cost of a sensor node is a very challenging
issue
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Hardware constraints
• A sensor node is made up of four basic components:
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sensing unit
processing unit
transceiver unit
power unit
• They may also have application dependent additional
components such as:
• location finding system
• mobilizer
• power generator
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Hardware constraints
• All of these subunits may need to fit into a matchbox-sized
module
• Apart from the size, there are also some other stringent
constraints for sensor nodes:
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consume extremely low power
operate in high volumetric densities
have low production cost and be dispensable
be autonomous and operate unattended
be adaptive to the environment
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Power consumption
• Sensor node lifetime dependence on battery lifetime
• Limited power source
• Replenishment of power resources
• might be impossible
• power conservation and power management take on
additional importance
• In other mobile ad hoc network ?
• Maybe important but not primary
• Can be replace by user
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Power consumption
• Power consumption can be divided into three domains
• Sensing
• Communication
• Data processing
• Sensing
• varies with the nature of applications
• Sporadic sensing might consume lesser power than constant
event monitoring
• complexity of event detection
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Power consumption
• sensor node expends maximum energy in data
communication
• Data transmission
• Data reception
• Data processing
• Energy expenditure in data processing is much less compared
to data communication
• the energy cost of transmitting 1 KB a distance of 100 m
• same as that for executing 3 million instructions
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Communication architecture
• sensor nodes are usually scattered in a sensor field
• Each sensor nodes has the capabilities :
• collect data
• route data back to the sink and the end users
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Routing protocol
• Power efficiency
• Data-centric protocols
• Flooding and gossiping
• Sensor protocols for information via negotiation (SPIN)
• Directed Diffusion
• Hierarchical protocols
• LEACH
• Network flow and QoS-aware protocols
• SAR
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Routing protocol
• Sensor networks are mostly data centric
• In data-centric routing, the interest dissemination is
performed to assign the sensing tasks to the sensor nodes
• There are two approaches used for interest dissemination:
• Sinks broadcast the interest
• sensor nodes broadcast an advertisement for the available data
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Data-centric protocols
• Flooding:
• each node receiving a data or management packet repeats it
by broadcasting
• unless a maximum number of hops for the packet is reached
• the destination of the packet is the node itself
• However, it has several deficiencies:
• Implosion
• Overlap
• Resource blindness
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A
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B
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Gossiping
• A derivation of flooding
• nodes do not broadcast but send the incoming packets to a
randomly selected neighbor
• randomly selected neighbor send the data
• Although this approach avoid the implosion problem
• by just having one copy of a message at any node
• it takes long time to propagate the message to all sensor
nodes
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Data aggregation
• solve the implosion and overlap problems
• Data coming from multiple sensor nodes are aggregated
• as if they are about the same attribute of the phenomenon
• when they reach the same routing node on the way back to
the sink
• Data aggregation can be perceived as a set of automated
methods of combining the data that comes from many sensor
nodes into a set of meaningful information
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SPIN
• Sensor protocols for information via negotiation
• The protocols are designed based on two basic ideas:
• sensor nodes operate more efficiently
• conserve energy by sending data that describe the sensor data
instead of sending the whole data
• SPIN has three types of messages:
• ADV
• REQ
• DATA
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Directed Diffusion
• queries the sensors in an on demand basis by using attributevalue pairs for the data
• Each sensor node then stores the interest entry in its cache
• timestamp field
• gradient field
• However, Directed Diffusion cannot be applied to all sensor
network applications
• The applications that require continuous data delivery to the sink
will not work efficiently
• since it is based on a query-driven data delivery model
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LEACH
• Low-energy adaptive clustering hierarchy
• minimizes energy dissipation in sensor networks
• Randomly select sensor nodes as cluster-heads
• The cluster head task is to manage communication among
member nodes of the cluster, data processing, and relay
processed sensed data to the Base Station
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SAR
• Sequential assignment routing
• The SAR algorithm creates multiple trees where the root of
each tree is an one hop neighbor from the sink
• The SAR algorithm selects the path based on :
• Energy resources
• Additive QoS metric
• packet’s priority level
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Conclusion & Future work
• The flexibility, fault tolerance, high sensing fidelity, low-cost
and rapid deployment characteristics of sensor networks
create many new and exciting application areas for remote
sensing.
• In the future, this wide range of application areas will make
sensor networks an integral part of our lives
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Refference
• I.F. Akyildiz et al., Wireless sensor networks: a survey,
Computer Networks 38 (4) (2002) 393–422
• Kemal Akkaya, Mohamed Younis, A survey on routing
protocols for wireless sensor networks, Ad hoc networks, 2005
- Elsevier
• I.F. Akyildiz, W. Su, A power aware enhanced routing (PAER)
protocol for sensor networks, Georgia Tech Technical Report,
January 2002, submitted for publication.
• C. Intanagonwiwat, R. Govindan, D. Estrin, Directed diffusion:
a scalable and robust communication paradigm for sensor
networks, Proceedings of the ACM Mobi-Com’00, Boston, MA,
2000, pp. 56–67
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