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Infrastructure Establishment (WSN)


November 3, 2016
Published By : Pratik Kataria
Categorised in:



The task of initiating collaborative environment for sensor network when that network is activated is called infrastructure establishment.
Sensor network consists of normal nodes and anchor nodes, where the normal nodes do not know their position but the anchor nodes are able to acquire their positions via external positioning device such as GPS. All sensor nodes including the normal node and the anchor node are randomly deployed in a sensor field, and they do not move after the initial deployment. In addition, each sensor node has a unique ID and the same data transmission radius

When sensor network is activated various task must be performed to establish necessary infrastructure that will allow useful collaborative work to be performed:

  1. Discovering other nodes
  2. Radio power adjustment to ensure adequate connectivity
  3. Cluster formation
  4. Node placement in a common temporal and spacial framework.

Some common techniques used to establish the network are:

  • Topology control
  • Clustering
  • Time synchronization
  • Localization

Topology control

•A sensor node that wakes up execute a protocol to discover which other nodes it can communicate with. (bidirectional)

•At initial state each node try to connect with neighbors according to the radio link capacity of its own.

•The neighbor is determined by the radio power of the node as well as local topology and other conditions that may degrade performance of the radio link.

•Sensor node are capable of broadcasting less that their maximum
possible radio power. (for energy saving and network lifetime)
Example : Homogeneous topology : all nodes with same transmission range.


Hierarchical architecture enables more efficient use of

sensor resources such as:

  • Frequency spectrum
  • Bandwidth
  • Power


1)Health monitoring of network is easy.

2)Identifying misbehaving node is easy.

3)Some nodes can act as watchdogs for other nodes.

4)Maintenance of network is easy.

Cluster formation:

1)Initially unique ids (UIDs) are assigned to each node

2)Node with higher ID than its uncovered neighbors declares itself as cluster head.

3)Cluster head nominated nodes then communicate with

each other.

4)Node that can communicate with two or more cluster heads may become gateway.

Gateway: node that aid in passing traffic from one cluster to other.

Uncovered neighbors: node that have not been already claimed by another cluster head.

Time Synchronization

Every node is operating independently so their clocks
may not be synchronized with each other.
It is important to run network efficiently

  • to detect events
  • for localization
  • estimating internodes distances.
  • to arrange TDMA schedule

In wired network NTP is used to achieve coordinated universal time (UTC).
In NTP highly accurate clock is mounted on one of the
machine of the network. This is not applicable for WSN :

  • No master clocks are available.
  • Inconsistent common delay.
  • Connections are variable/dynamic and unpredictable.

Time Synchronization

Time difference caused by the lack of common time
origin is called as clock phase difference or clock bias.
Methods for clock synchronization in WSN :
1) Clock phase diff estimation using three msg exchanges.
2) Interval method.
3) Reference broadcast.

Localization and Localization Services


To determine the physical coordinates of a group of sensor
nodes in a wireless sensor network (WSN)

Due to application context, use of GPS is unrealistic, therefore,
sensors need to self-organize a coordinate system


To report data that is geographically meaningful

Services such as routing rely on location information; geographic routing protocols; context-based routing protocols, location-aware services.

Localization in Wireless Sensor Networks

In general, almost all the sensor network
localization algorithms share three main phases


The distance estimation phase involves measurement techniques to estimate the relative distance between the nodes.
The Position computation consists of algorithms to calculate the coordinates of the unknown node with respect to the known anchor nodes or other neighboring nodes.
The localization algorithm, in general, determines how the information concerning distances and positions, is manipulated in order to allow most or all of the nodes of a WSN to estimate their position. Optimally the localization algorithm may involve algorithms to reduce the errors and refine the node positions.

Distance Estimation

There are four common methods for measuring in distance estimation technique:


ANGLE OF ARRIVAL method allows each sensor to
evaluate the relative angles between received radio signals

TIME OF ARRIVAL method tries to estimate distances
between two nodes using time based measures

TIME DIFFERENT OF ARRIVAL is a method for determining the distance between a mobile station and nearby synchronized base station

THE RECEIVED SIGNAL STRENGTH INDICATOR techniques are used to translate signal strength into distance.

Position Computation

The common methods for position computation techniques are:


LATERATION techniques based on the precise measurements to three non collinear anchors. Lateration with more than three anchors called multilateration.

ANGULATION or triangulation is based on information about angles instead of distance.

Properties Of Positioning & Localization

Physical position vs symbolic location
–System provide data about the physical position of a node (in some numeric coordinate system) or node learn about a symbolic location – for example, “living room”, “office 123 in building 4”.
–Is it, in addition, possible to match physical position with a symbolic location name (out of possibly several applicable ones).

Absolute vs relative coordinates
–An absolute coordinate system is valid for all objects and embedded in some general frame of reference. E.g. positions in the UTM (Universal Transverse Mercator) coordinates form an absolute coordinate system for any place on earth.
–Relative coordinates can differ for any located object or set of objects – a WSN where nodes have correct coordinates wrt each other but have no relationship to absolute coordinates is an example.
–To provide absolute coordinates, a few anchors (aka beacons or landmarks) are necessary (at least three for a 2D system). These anchors are nodes that know their own position in the absolute coordinate system.
–Anchors can rotate, translate, and possibly scale a relative coordinate system so that it coincides with the absolute coordinate system.

Localized versus centralized computation
–Are any required computations performed locally, by the participants, on the basis of some locally available measurements?
–Are measurements reported to a central station that computes positions or locations and distributes them back to the participants?
–Apart from scaling and efficiency considerations (both wrt computational and communication overhead), privacy issues are important here as it might not be desirable for a participant to reveal its position to a central entity

Accuracy and precision
–Positioning accuracy is the largest distance between the estimated and the true position of an entity (high accuracy indicates a small maximal mismatch).
–Precision of localization and position system is the ratio with which a given accuracy is obtained.
–Evidently, accuracy and precision values only makesense when considered together, forming the accuracy/precision characteristic of a system.

–A system can be intended for different scales, for example – in indoor deployment – the size of a room or a building or – in outdoor deployment – a parking lot or even worldwide operation.
–Two important metrics here are, the area the system can cover per unit of infrastructure, and the number of locatable objects per unit of infrastructure per time interval.


–For some positioning techniques, there are inherent deployment limitations.
–GPS, for example, does not work indoors; other systems have only limited ranges over which they operate.


Positioning systems cause costs:

  • in time (installation, administration),
  • space (device size, space for infrastructure),
  • energy (during operation), and
  • capital (price of a node and infrastructure).

Task driven Sensing

The purpose of a sensor system is often viewed as obtaining information that is as extensive and detailed as possible about the unknown parts of the world state.
Any targets present in the sensor field need to be identified, localized, and tracked.
All this data is to be centrally aggregated and analyzed.

This is a reasonable view when the potential use of this information is not known in advance, and when the cost of the resources needed to acquire and transmit the information is either fixed or of no concern.
Such a scheme, however, runs the danger of flooding the network with useless data and reduce limited resources from battery power to human attention.

There are obvious ways to be more selective in choosing what sensor nodes to activate and what information to communicate; protocols such as directed diffusion routing address exactly this issue for the transport layer of the network.
When we know the relevant manifest variables defining the world state—say, the position and identity of each target—then computing the answers to queries about the world state is a standard algorithm design problem

An algorithm typically proceeds by doing both numerical and relational (e.g., test) manipulations on these data, in order to compute the desired answer.
The quality of the algorithm is judged by certain performance measures on resources, such as time and space used.

Roles of Sensor Nodes and Utilities

Sensors in a network may take on different
Consider the following example of monitoring toxicity levels in an area around a chemical plant that generates hazardous waste during processing.
A number of wireless sensors are initially deployed in the region



The network may be tasked to monitor the maximum toxicity levels in the region.

To reduce the data traffic, individual toxicity detections from the sensors may be aggregated at an intermediate node, before being transmitted to the next node.

In many cases, including this one, the aggregated data is of the same size as an individual detection.

A sensor may take on a particular role depending on the application task requirement and resource availability such as node power levels.

As the node energy reserve or other conditions change, a sensor may take on a different role.

Information-Based Sensor Tasking

information-based-sensor-tasking-1Sensor Selection


Information-Driven Sensor Querying (IDSQ)


Joint Routing and Information Aggregation





The routing has to maximize information gain along the path.
A path toward the high information region may be more preferable than the shortest path.

Pratik Kataria is a budding programmer, web designer and developer.