Wireless sensor networks: a survey
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Transcript of Wireless sensor networks: a survey
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Wireless sensor networks: a survey
周紹恩指導教授 :柯開維1
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Outline• 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:• 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• 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 11
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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 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
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Hardware constraints• A sensor node is made up of four basic components:• 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:• 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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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 attribute-
value 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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