a survey of wireless sensor networks deployment techniques · 2018-02-19 · a survey of wireless...

DSTIS 2009

A survey of wireless sensor A survey of wireless sensor networks deployment techniquesnetworks deployment techniques

MichaMichałł Marks Marks

Institute of Control and Computation EngineeringWarsaw University of Technology

Research and Academic Computer Network (NASK)

September 4 – 7, 2009DSTIS - Decision Support for Telecommunications and Information Society

http://www.ia.pw.edu.pl/

A survey of wireless sensor networks deployment techniques 2September 4 - 7, 2009

DSTIS 2009Outline

• Introduction to positioning in Wireless Sensor Networks

• Key properties in WSN designing• Positioning taxonomy – classification criteria• Examples

coveragetracking

• Summary and conclusions


DSTIS 2009Previously on DSTIS

DSTIS 2008: WSN Localization Problem

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LOCALIZATIONGoal:Estimation of the network nodes location

Ad hoc network consisting of a set of sensors with

initially unknown positions


DSTIS 2009Positioning nodes in WSN

Different meaning of the „positioning”

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Goal:Positioning the nodes so as to meet the aim of successfully transferring data from the sources to the base station and, ultimately, to optimize some network performance metric.

DEPLOYMENT

A set of sensors to beplaced in considered area


DSTIS 2009WSN Positioning Classification - preliminary

LOCALIZATIONLOCALIZATION DEPLOYMENT(PLACEMENT)DEPLOYMENT(PLACEMENT)

WSN POSITIONINGWSN POSITIONING


DSTIS 2009Definition of Wireless Sensor Network

In the past, a number of early, mostly US-based research projects established a de facto definition of a wireless sensor network as a large-scale ad hoc, multi-hop, unpartitionednetwork of largely homogenous, tiny, resource-constrained, mostly immobile sensor nodes that would be randomly deployed in the area of interest.

Romer, K.; Mattern, F., The design space of wireless sensor networks, IEEE Wireless Communications, Volume 11, Issue 6, 2004, 54 - 61


DSTIS 2009

……Mobile Sensor Networks

WSN world is changing

Mobile Sensor Networks

Wireless Sensor NetworkWireless Sensor Network

Wireless Sensor and Actor Networks

Wireless Sensor and Actor Networks

Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks

1.Wang, Y., Dang, H., Wu, H. A survey on analytic studies of Delay-Tolerant Mobile Sensor Networks: Research Articles. Wirel. Commun. Mob. Comput. 7, 10 (Dec. 2007), 1197-1208.

2.Akyildiz, I. F., Kasimoglu, I. H., Wireless Sensor and Actor Networks: Research Challenges, Ad Hoc Networks Journal, 2, 4 (Oct. 2004) pp. 351-367.

3.Akyildiz, I. F., Melodia, T., Chowdhury, K. R., A survey on wireless multimedia sensor networks. Comput. Netw. 51, 4 (Mar. 2007), 921-960.

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DSTIS 2009Initial assumptions and WSN development

WSN DEFINITION PROPERTIES

large-scale ad hoc, multi-hop, unpartitioned network of largelyhomogenous, tiny, resource-constrained, mostly immobile sensor nodesthat would be randomly deployedin the area of interest.

1. NETWORK SIZE

2. NETWORK TOPOLOGY

3. HETEROGENITY

4. SIZE, RESOURCES

5. MOBILITY

6. DEPLOYMENT


DSTIS 2009WSN development: 1. Network size

The network size may vary from a few nodes to thousands of sensor nodes.The number of nodes participating in a sensor network is mainly determined by requirements relating to network connectivity and coverage, and by the size of the area of interest.

Possible values: all from a few nodes to thousands of nodes

Examples:Application Size (number of nodes)

Torre Aquila (monitoring Heritage Buildings) 16Glacsweb (glacier monitoring) 32Argo (ocean monitoring) 3338


DSTIS 2009Example 1: Argo Project #1

Argo is a global array of 3,000 free-drifting profiling floats that measures the temperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection.

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DSTIS 2009Example 1: Argo Project #2


DSTIS 2009WSN development: 2. Network topology #1

One important property of a sensor network is the maximum number of hops between any two nodes in the network. In its simplest form, a sensor network forms a single-hop network, with every sensor node being able to directly communicate with every other node. In multi-hop networks nodes may forward messages over multiple hops.

The sensor network architecture can be flat where all sensors play the same role in communication – all nodes acts as routers. We can also consider a tired architecture. The most common is two-tier where sensors are split into clusters; each is led by an cluster head node.

Possible values: I dim single-hop, multi-hop, II dim flat, layered (tiered)


DSTIS 2009WSN development: 2. Network topology #2

Examples:Application Network topology

Torre Aquila (monitoring Heritage Buildings) flat, ad-hoc, multi-hopGrape (Agricultural Wireless Sensor Network) two-tier, multi-hopGlacsweb (glacier monitoring) two-tier, multi-hop


DSTIS 2009Example 2: Glacsweb Project #1

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DSTIS 2009Example 2: Glacsweb Project #2

The base station is located on the surface of the glacier. Due to the significant radio losses in the upper ice layer, the nodes are unable to communicate directly with base station. In order to establish (or enhance) these communication links, the base station is connected to some of the nodes (called anchor nodes) via a serial cable. These anchor nodes are responsible for communicating with the remaining network on behalf of the base station.

Two-tier network configuration

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DSTIS 2009WSN development: 3. Heterogenity

Early sensor network visions anticipated that sensor networks would typically consist of homogeneous devices that were mostly identical from a hardware and software point of view.However, in many prototypical systems available today, sensor networks consist of a variety of different devices. Nodes may differ in the type and number of attached sensors; some nodes may act as gateways to long-range data communication networks (e.g., GSM networks or satellite networks).Possible values: homogeneous, heterogeneous

Examples:Application Heterogenity

Torre Aquila (monitoring Heritage Buildings) heterogeneousArgo (ocean monitoring) homogeneousGlacsweb (glacier monitoring) homogeneous


DSTIS 2009Example 3: Torre Aquila

The system contains many kinds of sensors, whose operation is quite different. Deformation and environmental parameters can be sampled at a low rate, but vibration must be monitored at a high rate, which consequently demands efficient reporting of the resulting high volume of data.


DSTIS 2009WSN development: 4. Size, resources #1

Depending on the actual needs of the application, the formfactor of a single sensor node may vary from the size of a shoe box (e.g., a weather station) to a microscopically small particle (e.g., for military applications). Similarly, the cost of a singledevice may vary from a few Euros to a hundreds of Euros.Varying size and cost constraints directly result in corresponding varying limits on the energy available, as well as on computing,storage, and communication resources. Possible values: brick, matchbox, grain, dust

Examples:Application Node length Node cost

Torre Aquila (monitoring Heritage Buildings) 13 cm110 cm16 cm

>=120$Argo (ocean monitoring) ~ 15000$Glacsweb (glacier monitoring) ~ 320$


DSTIS 2009WSN development: 5. Mobility

Sensor nodes may change their location after initial deployment.Mobility can result from environmental influences such as wind or water, sensor nodes may be attached to or carried by mobile entities – passive mobility.Sensor nodes may possess automotive capabilities – activemobility.

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DSTIS 2009WSN development: 5. Mobility

Mobility may apply to all nodes within a network or only tosubsets of nodes. The degree of mobility may also vary from occasional movement with long periods of immobility in between, to constant travel.

Possible values: I dim active, passiveII dim mobile, stationary, mixed.

Examples:Application Mobility

Wildsensing – University of Oxford passive, mixed, 30 mobile, 28 stationary

Torre Aquila - University of Trento stationaryMobile Sensor Swarms – Univ. of Notre Dame mobile


DSTIS 2009WSN development: 6. Deployment

The deployment of sensor nodes in the physical environmentmay take several forms. Nodes may be deployed at random (e.g., by dropping them from an aircraft) or installed at deliberately chosen spots. The actual type of deployment affects important properties such as the expected node density, node locations, regular patterns in node locations, and the expected degree of network dynamics.

Possible values: random, deterministic.

Examples:Application Deployment

Argo (ocean monitoring) randomTorre Aquila (monitoring Heritage Buildings) deterministicGlacsweb (glacier monitoring) deterministic


DSTIS 2009From properties to classification

large-scale ad hoc, multi-hop, unpartitioned network of largelyhomogenous, tiny, resource-constrained, mostly immobile sensor nodesthat would be randomly deployedin the area of interest.

1. NETWORK SIZE

2. NETWORK TOPOLOGY

3. HETEROGENITY

4. SIZE, RESOURCES

5. MOBILITY

6. DEPLOYMENT

PROPERTIESWSN DEFINITION

3. HETEROGENITY

5. MOBILITY

6. DEPLOYMENT


DSTIS 2009Classification criteria for WSN positioning techniques

1. HETEROGENITY

3. DEPLOYMENT

2. MOBILITY

4. OBJECTIVES

Homogeneous, heterogeneous

Stationary, mobile, mixed networks

Deterministic, random

• Area coverage• Network connectivity• Network longevity• Data fidelity• Ability to tracking the objects• Fault tolerance• Effective transmission• …


DSTIS 2009Classification tree

Positioning in Wireless Sensor Networks

Stationary networks

Mobile networks

Mixed networks (some nodes are mobile)

Homogeneous nodes

Heterogeneous nodes

Deterministic Deployment

Random Deployment

Stationary networks

Mobile networks

Coverage

Tracking

Fault tolerant

Coverage topology control

Localization


Coverage

Tracking

Fault tolerant


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Coverage

Tracking

Fault tolerant


DSTIS 2009Coverage #1


Stationary networks

Mobile networks


Homogeneous nodes

Heterogeneous nodes


Random Deployment

Stationary networks

Mobile networks

Coverage

Tracking

Fault tolerant


Localization


Coverage

Tracking

Fault tolerant


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Coverage

Tracking

Fault tolerant


DSTIS 2009Coverage #2

Maximal coverage of the monitored area is the objective that hasreceived the most attention in the literature. Some of the papers, especially early ones, use the ratio of the covered area to thesize of the overall deployment region as a metric for the qualityof coverage.


DSTIS 2009Coverage -> Tracking

Since 2001, however, most work has focused on the worst case coverage, usually referred to as least exposure, measuring the probability that a target would travel across an area or an event would happen without being detected.


DSTIS 2009Example – sensor repositioning to improve coverage #1

Lets assume that we have a mobile sensor network and the goal is to maximize the area covered with minimal overhead in terms of travel distances and inter-sensor message traffic. The main idea is that each sensor assesses the coverage in its neighborhood and decides whether it should move to boost the coverage. To assess the coverage, a sensor node creates a Voronoi polygon with respect to neighboring sensors.



The intersection of the disk that defines the sensing range andthe Voronoi polygon represents the area the sensor can cover. Ifthere are uncovered areas within the polygon, the sensor shouldmove to cover them.



So, the sensor node is pulled towards the farthest Voronoi vertex (point A) to fix the coverage hole in the polygon. However, the sensor will be allowed to travel only a part of a distance between the node S and point A. The authors proposed 3 different methods how to calculate this distance.



Initial deployment Final deployment

Wang, G., Cao, G., La Porta, T., Proxy-Based Sensor Deployment for Mobile Sensor Networks, IEEE MASS, October 2004


DSTIS 2009Tracking - example


Stationary networks

Mobile networks


Homogeneous nodes

Heterogeneous nodes


Random Deployment

Stationary networks

Mobile networks

Coverage

Tracking

Fault tolerant


Localization


Coverage

Tracking

Fault tolerant


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Random Deployment

Coverage

Tracking

Fault tolerant


Localization


Coverage

Tracking

Fault tolerant


DSTIS 2009Example – monitoring movements #1

The facility is modeled as a circle ofradius 1 centered at the origin. It is assumed that any sensor placed inside the facility will not be able to operate. Two roads servethe facility, one horizontal goingEast, one vertical going North.

Monitoring movements in and out of a facilityserved by two roads

Jourdan, D., de Weck, O., Multi-objective genetic algorithm for the automated planning of a wireless sensor network to monitor a critical facility



Objective 1: CoverageThe first objective is the coverage, by which is meant the ability of the networkto monitor movements in and out of thefacility. A series of radial lines stemmingfrom the facility are generated, andrepresent the possible directions fromwhich agents can enter or exit the facility. A sensor covers a line if its distance withthe line is less than sensing range. Thecoverage is equal to the number of linescovered by the sensors, divided by thetotal number of lines.



Objective 2: SurvivabilityThe second objective is thesurvivability of the network, by whichis meant the likelihood that sensorswill not be found. Each point in thearea is assigned a probability ofdetection. This probability dependson the proximity of the facility or theroads. It is assumed that if a sensor is placed close to a road (wheremost of the activity takes place) or to the facility, it is more likely to be found and disabled.



Objective 3: Number of sensors

Solution:



Solution Coverage Survivability Number of sensorsb 0,99 0,74 9c 0,96 0,66 7d 1,00 0,44 5


DSTIS 2009Conclusions

The deployment problem is one of the most fundamental issue in WSN designing.

How many wireless sensor nodes should be used and where should they be placed in order to optimize network performance? This is a difficult question to answer for a decision maker due to conflicting objectives of deployment costs, overallnetwork lifetime and wireless transmission reliability.

I have tried to present a categorization of various strategies for positioning nodes in WSNs. We have considered stationary, mobile and mixed networks with homogenous or heterogeneous nodes. We have made an attempt to identify the various objectives and enumerate the different models and formulations.


DSTIS 2009

Thank You for attentionThank You for attention


DSTIS 2009Questions about deployment

How many sensor nodes are needed to meet the overall system objectives?

For a given network with a certain number of sensor nodes, how do we precisely deploy these nodes in order to optimize network performance?

When data sources change or some part of the network malfunctions, how do we adjust the network topology and sensor deployment?

Cassandras, C.G. Wei Li, Sensor Networks and Cooperative Control, 44th IEEE Conference on Decision and Control, 2005, 4237- 4238


DSTIS 2009WSN development: 4. Size, resources #2

ARGO TORRE AQUILA GLACSWEB


DSTIS 2009

a survey of wireless sensor networks deployment techniques · 2018-02-19 · a survey of wireless...

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