sensor networks - unina.it

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Sensor Networks Lessons 3-4 Prof. Sabato Manfredi [email protected] +390817683845

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Page 1: Sensor Networks - unina.it

Sensor NetworksLessons 3-4

Prof. Sabato [email protected]+390817683845

Page 2: Sensor Networks - unina.it

Forest Fire Detection

Body Networks for healthcare applications

Tracking of robots, vehicles in closed areas

APPLICATIONS

Amount of Data Generated by Nodes: nodes can send few Bytes per hour, or many KBytes per second….

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Event Triggered Reporting Event Detection / Control

Loose Reporting Estimation of Spatial and

Temporal Processes / Control

Frequent Periodic Reporting Monitoring / Tracking / Control

TYPE OF REPORTING

APPLICATIONS

Taxonomy

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Event Triggered Reporting delay

Loose Reporting data losses

Frequent Periodic Reporting network throughput

TYPE OF REPORTING

PERFORMANCE REQUIREMENT

Taxonomy

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Event Detection

Density of nodes: the event is detected with given probability;

Coverage, related to sensing range of nodes and event type, distributed localisation algorithms

connectivity, related to transmission range of nodes

The samples can be received by the sink(s) with given probability;

communication protocols

responsiveness, related to event type: the report timely reaches the sink(s)

TYPE OF REPORTING SN ISSUSES

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Estimation of Processes

Density of nodes: the process is accurately estimated;

Connectivity, related to transmission range of nodes

Coverage, related to sensing range of nodes

The samples can be received by the sink(s) with given probability;

Data processing, related to process type

communication protocols

The sampling frequency must ensure the process evolution is tracked;

Responsiveness, related to process type, the report timely reaches the sink(s)

Tracking: Estimation of Processes Event Detection

TYPE OF REPORTING SN ISSUSES

Page 7: Sensor Networks - unina.it

Probability of false alarm < 0.1 – 0.001

Probability of missed detection < 0.1 – 0.001

Localization precision < 100 – 1 m Latency < 0.1 – 10 s

Network lifetime > months - years

The different types of requirements make SN features very application-dependent.

REQUIREMENT EXAMPLES

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TAXONOMY

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Wireless Ad Hoc Networks

MANETs (Mobile Ad Hoc Networks) are formed dynamically by anautonomous system of nodes connected via wireless links without using anexisting network infrastructure or centralized administration.

Nodes are connected through “ad hoc” topologies, set up and clearedaccording to user needs and temporary conditions.

MANETS (1/3)

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Main Features

Fixed infrastructure is not needed

Unplanned and highly dynamical

Nodes are “smart” terminals (laptops, …)

Real-time or non real-time data, multimedia, voice, …

Every node can be either source or destination of information

Every node can be a router toward other nodes

Energy is not the most relevant matter

Capacity is the most relevant matter

MANETS (2/3)

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Applications

Emergency Services – nodes are mobile over large areas

Home and Enterprise Networks – nodes are laptops

Attendees in a conference room sharing documents and other information via their laptops and handheld computer;

Armed forces creating a tactical network in unfamiliar territory for communications and distribution of situational awareness information;

Small sensor devices located in animals and other strategic locations that collectively, monitor habitats and environmental conditions;

Emergency services communicating in a disaster area and sharing video updates of specific locations among workers in the field, and back to headquarters.

IEEE 802.11/Wi-fi

MANETS (3/3)

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Nodes are “smart” terminals (laptops, …)

Real-time or non real-time data, multimedia, voice, …

Every node can be either source or destination ofinformation

Every node can be a router toward other nodes

Energy is not the most relevant matter

Capacity is the most relevant matter

WSNS VS MANETS (1/2)

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WSNS VS MANETS (2/2)

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HETEROGENEOUS NETWORKS

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PROTOCOL STACK FOR SNS (1/2)

Rb : The channel capacity (bit rate)

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PROTOCOL STACK FOR SNS (2/2)

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SINGLE-SINK SINGLE-HOP (1/3)

N : The number of nodes Rb : The channel bit rate

αA : Factor taking into account of the overhead introduced by all protocol

stack layers SA : Maximum data throughput measured at the application layer

We consider a WSN where nodes are requested to

send their samples (composed of D bytes each) taken

from the monitored space every TR seconds.

Let us give a simple and approximate evaluation of the capacity of a single-

sink WSN, defined in terms of maximum number of nodes that can be

attached to the sink.

N ?

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SINGLE-SINK SINGLE-HOP (2/3)

N : The number of nodes Rb : The channel bit rate

αA : Factor taking into account of the overhead introduced by all protocol

stack layers SA : Maximum data throughput measured at the application layer

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SINGLE-SINK SINGLE-HOP (3/3)

To give a numerical example, assume Rb = 250 Kbit/s, TR = 1 s, αA=0.1,

D=3; then the maximum number of nodes is approximately 1000.

On the other hand, if TR=10 ms, then N can not exceed 10.

It is clear that the requirements set by the application scenario play a very

relevant role when defining the capacity of a single-sink WSN.

In the case discussed above, the N nodes are all within range of the sink.

If the transmis- sion range of links between sink and nodes is R, then the

density of nodes is

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SINGLE-SINK MULTI-HOP

N : The number of nodes Rb : The channel bit rate

αA : Factor taking into account of the overhead introduced by all protocol

stack layers SA : Maximum data throughput measured at the application layer hm : Average number of hops per data sample

If a node can send its sample to the sink through h hops, then the delivery

of the data sample requires h transmissions. Let us denote by hm the

average number of hops per data sample taken from the field and if no

smart reuse of radio resources is introduced, then we have for a single-sink

multi-hop WSN:

The capacity of the network is reduced by a factor of hm.