Node Positioning

Application for Wireless Networks Industrial Plants

Pedro H. G. Coelho, Jorge L. M. do Amaral and José F. do Amaral

Rio de Janeiro State University, UERJ, Department of Electronics and Telecommunications,

Rua São Francisco Xavier, 524 – Sala 5027E, 20550-900, RJ – Rio de Janeiro, Brazil

Keywords: Wireless Networks, Node Positioning, Artificial Immune Systems.

Abstract: This article discusses the positioning of the nodes of a wireless network of an industrial plant for the

network to meet the application requirements, particularly with respect to coverage characteristics and

reliability. Issues involving these two parameters are investigated and it is intended to submit proposals

using the concepts of computational intelligence to solve the problem.

1 INTRODUCTION

The possibility of using wireless network has been

widely discussed in the areas of industrial

automation, environmental monitoring, and location

of road vehicles among others. The great advantage

of not using cable for data transmission is the ease of

network installation in all environments, including

those where it is not possible to lay cables, be for the

difficulty of access, or for being a dangerous area or

not allowed access. Another advantage is the ease of

maintenance of equipment. In the listed applications,

it is of paramount importance the safety, reliability,

availability, robustness, and network performance in

carrying out the monitoring and process control.

That is, the network cannot be sensitive to

interference or stop its operation because of an

equipment failure, nor can have high latency in data

transmission and ensure that the information is not

lost (Zheng and Myung, 2006), (Santos, 2007).

A network of wireless smart sensors is

responsible for conducting the monitoring of a

process or an environment, process the collected

information and send it to other sensors or routers

closer to the gateway. The sensors are powered by

batteries and positioned according to the process to

be monitored (Gomes, 2008).

Data transmission in a wireless network in

today's industrial automation is faced with the

problem of interference generated by other

equipment and obstacles. In an attempt to minimize

these effects, various methods of intermediate nodes

positioning are used. The intermediate nodes or

routers are responsible for making the routing of

data, generated by sensors in the network to the

gateway through hops, directly or indirectly. Such

devices are responsible for meeting the safety,

reliability and robustness criteria of the network and

are of paramount importance in directing data

transmission. However, they can leave all or a great

part of the network dead, if they have any fault

(Hoffert et al., 2005).

Most of the presented solutions to this problem

use optimization algorithms to find the smallest

number of routers needed to make the network meet

the criteria related to the decrease of energy

consumption of each node. Moreover, monitoring

the total area, simplifying the network with the

lowest cost, meeting the traffic demand not evenly

distributed, reducing the latency of the data, the

reduction of computational complexity, minimizing

the burden placed on the nodes and maximizing the

number of nodes that can communicate with the

gateway are also key issues in the problem (Youssef

and Younis, 2007), (Molina et al., 2008). These

solutions typically face problems of scalability and

changes of the network configuration the over the

years. Thus, for each network configuration it would

be necessary to develop a specific solution in

accordance with new obstacles, positioning of the

sensor nodes and, consequently, new positions for

the routers.

This article is divided into four sections. This

section is an introduction to the problem of

positioning nodes in wireless networks. Section two

discusses the importance of studying node

291

H. G. Coelho P., L. M. do Amaral J. and F. do Amaral J..

Node Positioning - Application for Wireless Networks Industrial Plants.

DOI: 10.5220/0004095402910294

In Proceedings of the 14th International Conference on Enterprise Information Systems (ICEIS-2012), pages 291-294

ISBN: 978-989-8565-10-5

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

positioning. In section three possible solutions to the

problem using computational intelligence (CI) are

discussed. The forth section closes the paper

presenting research directions and preliminary

conclusions.

2 NODE POSITIONING ISSUES

This section briefly discusses the positioning of

nodes characteristics and its main constraints.

Why study the positioning of the nodes? For the

network to meet the application requirements,

especially regarding reliability and coverage issues.

Positioning of the nodes can cause a dramatic impact

on the efficient operation of networks.

The positioning of the nodes can be static, which

is done before the network operation, or dynamic,

where the repositioning of nodes continues on the

network in operation.

Static positioning of the nodes depends on the

method of nodes distribution, for instance controlled

or randomized. It also varies with the optimization

objective which may include the coverage area,

connectivity, longevity or data fidelity. The role of

node in the wireless network should also be taken

into account in the positioning process e. g. the node

can act as a sensor repeater, a base station or cluster-

head node. Questions such as where and when to

relocate nodes naturally arise and the characteristics

of the network also play an important role in the

whole process.

One has to define the network coverage or in

other words the accessibility to the gateway. The

critical nodes are those for which its load is

overwhelming and the sensitivity of the network to a

loss of such a node is high. Fault tolerance is also a

key issue and it is of paramount importance to know

what happens if a node fails. In such a case it is

important to know if an alternative path exists for

those paths having that faulty node. Determining the

number and the positioning of repeater nodes is also

an information one should have.

For industrial wireless networks every node must

be able to communicate with the gateway, either

directly or through other nodes, so that the targeted

coverage should be equal to 100 %.

As far as the used criteria are concerned for each

of such networks, every node must have a certain

number of neighbors in order to increase the

availability of alternative paths. That means also that

a number of network nodes must be in direct

connection with the gateway. The number of hops

for which a message reaches a node to the gateway

has to be closely monitored once the increase in the

number of hops raises the message latency.

Depending on the refresh rate of the measurements,

in case of wireless sensor applications, this can be an

important issue. Also the number of retransmissions

from other nodes necessary for reaching the gateway

should be carefully considered as increasing the

number of retransmissions may shorten the battery

life.

In terms of fault tolerance it is important to know

what percentage of the network that is still working

if a particular node fails. What is the most critical

node on the network in relation to this criterion?

Those issues are to be considered in the building

of the node positioning for industrial wireless

networks.

3 CI BASED PROPOSALS

This section presents proposals for solving the

problem of positioning nodes for wireless industrial

networks employing computational intelligence

techniques. Such techniques are very promising for

application to the problem at hand because they

allow consideration of heuristic optimization issues

related to the theme.

The problem of positioning nodes is an NP-Hard

(Molina, 2008) and in view of this, it is usual to use

heuristics and stochastic optimization schemes. Thus

potential techniques applicable to the solution of the

problem involve those related to computational

intelligence such as genetic algorithms, collective

intelligence, such as ant colony optimization,

artificial immune systems and others. Before

proceeding it is necessary to emphasize an important

feature of the problem of positioning nodes in

wireless networks in industrial environments. Note

that in this case, the nodes in the network are

positioned at locations to be instrumented and

connectivity with the central node, usually located in

the control room, it is absolutely necessary

otherwise the consequences can be devastating. This

situation is distinct from a network of wireless

computers only for INTERNET access in which

connectivity can be lost and then resumed without

major losses to the user, since the greatest interest is

to achieve a high throughput.

3.1 Node Positioning using Artificial

Immune Systems

The immune system is one of most important ones

for the survival of humans and animals. It has the

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task of fighting the invaders, which cause diseases

through complex mechanisms. Such mechanisms are

complementary and fit to perform the recognition of

pathogens (viruses, bacteria, foreign molecules etc.)

and inhibit its action in the body of the individual

and are divided into (Amaral, 2006) (Castro, 2001):

1. Recognition of pathogen - is accomplished by

lymphocytes, i.e. B and T cells that have receptors

for the purpose of joining the pathogen to

subsequently eliminate it;

2. Affinity maturation of lymphocyte receptors

and pathogen - there will be hypermutation receptors

so that they are able to fit "perfectly" to the antigen;

3. Cloning of the antibody with higher affinity -

cloning of lymphocytes that are better suited to the

pathogen;

4. Distinction between self and non-self - this

mechanism is of paramount importance for the

individual able to survive without any autoimmune

disease that destroys the cells and proteins of the

organism itself. It will make the distinction between

body proteins and the invaders;

5. Immunological memory - is a database stored

in the memory immune receptors, which act more

quickly and effectively against the next infection

caused by the same pathogen.

The artificial immune systems exploit

mechanisms found in natural immune systems to

develop techniques for solving problems. The

natural immune systems provide protection against

numerous pathogens such as viruses, bacteria and

others.

Some basic concepts of natural immune systems

will be described so that we can develop the

application in node positioning. Antigens are

substances that are not recognized by the immune

system as the body itself. There are two types of

immune systems the innate and the adaptive. The

first is the first line of defense of the living organism

and reacts similarly to different pathogens such as

the skin. Note that some pathogens cannot be fought

by the innate immune system. The adaptive system

fight against specific pathogens. Its main

components are B cells which produce antibodies

and T cells that attack the abnormal cells. The

response of the innate immune system remains

constant, the adaptive gives immunity against re-

infection of the same infectious agent. Pathogens or

molecules present antigens that are recognized by B

cells. Note that the marriage is not always perfect.

Since the antigen recognized, the B cell begins to

produce antibodies. Each B cell produces only one

type of antibody. For example, antibody to influenza

virus is different from that for pneumonia. The more

efficient antibodies are cloned.

Now an algorithm using artificial immune

system techniques will be described.

The algorithm is as follows:

1 - Initialization: Original placement or pattern

of antibodies.

2 - Training: Presentation of antigens for the

iterative network of antibodies against antigens and

antibodies.

3 - Competition: winners antibodies in accordan-

ce with an affinity function

4 - Cloning; reproducing the efficient antibodies.

5 - Convergence: each antibody is associated

with an antigen and each antigen antibody should

have a winner within a minimum defined distance.

6 - Pruning: After all training unrelated antibody

with any antigen is removed.

Preliminary tests indicate that the above proposal

is satisfactory.

4 CONCLUSIONS

The artificial immune systems are algorithms

inspired by the functioning of the human immune

system to solve optimization problems, pattern

recognition and others. The most widely used

algorithms in solving the problems mentioned above

are the immune network algorithms, clonal selection

and negative selection (Castro and Timmis, 2002).

The artificial immune networks are algorithms that

mimic the functioning of the immune network in

combating human infectious diseases in slaughter.

This network provides human immune B cells

capable of recognizing and to recombine in the

absence of the pathogenic agent, thereby forming a

network capable of eliminating the invaders. They

are formed in accordance with the degree of affinity

between B cells. If the affinity between them is high,

then the cell B is joined to the network, otherwise it

will be repelled away from the network. This action

of union or inhibition of B cells occur until the

network stabilizes and so could fight off diseases.

The purpose of this paper is to solve the problem of

positioning nodes in wireless industrial networks

using artificial immune, based on the human

immune system. The algorithms based on immune

networks have very desirable characteristics in

solving this problem, among which we mention:

scalability, self-organization, learning ability and

continuous treatment of noisy data. It is intended to

build positioning algorithms based on models of

artificial immune networks (Castro 2001), aiming to

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get the best settings for a wireless network industry,

positioning the router nodes in the network, so that

all devices to communicate with gateway without

loss of information.

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