elephant swarm optimization in wireless sensor...

Elephant Swarm Optimization in Wireless Sensor Network to Enhance Network Lifetime

1

Chapter-4

Network Lifetime Enhancement using Elephant Swarm

Optimization in Wireless Sensor Networks

4.1 Introduction

This chapter describes the research work done by author and it has been dedicated to

present the real time implementation of the proposed methodology, its mathematical

formulation, system integration and validation. In this chapter the author has intended to

express his methodological approach for obtaining its proposed cross-layered elephant

swarm optimization based lifespan maximization of Wireless sensing networks (WSNs).

As discussed earlier, the presented research work has been developed with an

expectation of lifespan maximization and its QoS behaviour for overall system

optimization. The presented research work has been developed by considering the

advantageous features of evolutionary computing. Elephant is a species that exhibits a

very sound and effective biological nature and few of the dominating characteristics are

like their memory capability, leadership or opting ion of clan leader, group leading and

ultimately change of leadership etc. These all types of specific characteristics could play

a vital role in network optimization and its lifespan enhancement. Evolutionary

computing has ignited a new scenario for research and development in numerous

engineering segments. Considering the evolutionary characteristics of elephant swarm

behaviour, here in this research work a robust cross-layered design has been developed.

The overall system has been developed while considering the homogenous network

conditions and has been simulated with various operating parameters. On the other hand

in order to justify the robustness of the proposed work, here in this research the author

has developed PSO based cross-layered design as well as most popular protocol, called as


2

LEACH. The overall system has been developed over SENSORIA, a robust WSNs

simulation platform with C# programming language.

4.2 Elephant’s Swarm Behavior

As we know that the elephants are the largest living mammal on land. They live in an

organization which is very much advance and need a very good level of interaction

among the individuals. They live in a society which is known as "fluid-fission-fusion"

society, as the name suggest the family units are regularly being divided and again

reunited while they are meeting with different individuals at the same time on a daily

basis. For this they require an advance step of interaction and recognition to allow each

and every individual to be a mediator between the complex relationships they expand

with the other individuals.

Social organization among the elephants is characterized by the closeness and the

intimacy between them and is divided into three types. The most valuable grouping is

“family-unit” which contains at least two related females (See Fig: 4.1) of their offspring.

Males cannot be the part of this family unit but either they combine together of live

solitary.

Figure 4.1 Group exhibitions in Elephants clan

A family may consists of more than 10-to-50 individuals and the level of

interaction between them is well organized and in coordinated manner. This type of

interaction generally includes offspring care, teamwork, resource acquisition and group

defense, and all this include decision making which is made by the powerful "matriarch".


3

The matriarch is the main female leader of the group who is the wisest and the

oldest and thus the most experienced. She makes every decision which includes safety,

movement and resource acquisition.

"Kinship groups" which is also known as "Bond groups", are the groups which

contain those individuals who are related genetically. These groups are formed due to

weakness in the family and they thus divided by the fission. A “clan” which consists of

100-250 members is a combination of kinship group and the family which shares same

shelter range mainly during a dry season. They eat together as a large social gathering

when the resources are less and once the resources become available they became a big

social organization. During the migration period 1000 members may come together for

the protection purpose and supremacy during the migration process, stated by Wilson

(2000).

Altruism

Within a family group there is a large degree of unselfishness and cooperation which

relates to the family opting ion. This leads to a conclusion that a family member will help

the other family member to increase its life time, number of offspring and thus they help

to maximize the family member’s gene contribution to the future generation, but they

only do this at the cost of their own survival. In this every young family members are

treated equally and allowed breastfeeding from the other females within the group and

their mother as well. Young females in the group act as “aunts” whose role is to make

sure that the new born members behave by denying them to run ahead of the group and

wake them up after the afternoon nap.


4

Fig 4.2 Matriarch of Elephant (right) protecting members of the herd from danger

Basically elephants are taking very care to all the family of the members, and they are

following one very sensitive and sentimental behavior is that mixing parental caring. One

more unselfish futuristic is observed and identified over the elephants is that the daring

behavior of the feminine head, that protects the whole group members or group by

standing within the front once there's any danger (given in Fig 4.2).

This is very intense social care and un-selfishness wherever the independent elephant

isn't simply revealing herself to danger for the purpose alternative member however is

additionally serving to the fitness of fifty relations or the subordinates.

Interaction

Interaction is one of the most significant styles of socio characteristics in elephants and

also the same thing is expected by the competent use of their senses. Interaction is most

crucial because it makes a bunch to stay an eye fixed on the defensive territories,

following and controlling their relatives and convincing their procreative state and create

the females to go together with the young members prior to weaning. They so need an

oversized interaction network owing to their system which might send the data regarding

their spirit, feelings, physical state and additionally transit their feelings and intentions.


5

4.3 Social Behavior and Interaction in Elephants

Acoustic Interaction

The interaction which deals with the production of sound and hearing is known as

Acoustic or Audio interaction. Elephants generally emit wide range of sound with diverse

intensity and for different purpose such as coordinating the movement, telling their needs,

attracting the mates, etc.

They emit sounds which include trumpets, growls, shrieks, squeals, and least frequency

vocalizations. Rumbling and growling are the two most generally used vocal sounds in

elephants and is used for the interaction between the family members and the individuals.

This can also be used as a disciplinary measure between the females and the calves,

presented by Wilson (2000).

Angry Elephants Trumpeting & Rumbling

It has been discovered by the scientists that the elephants produce an infrasonic sound

which ranges from 1- 20 Hz that is the out or human hearing capacity and can travel over

large distance and seismic signals, which are just like small earthquake and allows each

elephants to position themselves in relation to their own location, which is described by

Braden (2003).

A study reveals that the least frequency sounds transmitted between the females is

generally used as a reproductive strategy by the males, especially in the African

Elephants. The intensity of this sound depends on the reproductive state of the female.

Males generally use this vocalization as a way to search the group with high vocal

production and this indicates they are close to ovulation period. Males rely highly on the

interaction among the group by "eaves-dropping" so that there is high chance of locating

a female in the proximity, using visual and chemical cues are more reliable signals, stated

by Leong et. al. (2003).


6

Studies let us know that “eaves-dropping” method provides opportunity to

distinguish the individuals by co specifics and was supported as playback calls from

individuals and kinship group which resulted in a strong positive reaction of the elephants

which is used in the experiment, and it is presented by McComb et. al. (2000). Therefore,

this indicated that elephants have a large and organized network since they can

accumulate the knowledge to distinguish the signals from the huge population of the co-

specifics.

Fig 4.3 Trunk raised in threatening stance

They also do visual interaction such as posture, expression, movement of ears,

jaws and trunk, and it also refers to hoe the elephant’s use their sense of sight to

determine what message is the individual trying to give.

Interaction among the individuals as well as the rivals to display threat can be

determined by the Head and Trunk postures (see Fig 4.3).


7

The visual signals can be of high or least intensity, at least intensity elephants stand tall

and at high intensity or during threat they move forward with lifting their ears and the

trunk forward and runs towards enemy. The "forward trunk swish" is used for a small

rival where trunk is rolled up and lashed forward, which is stated by Wilson (2000).

Trunk is the most vital part in the visual interaction. To the signal importance they

will appear tall with leader high above the shoulders and the wide spread ears, while a

subordinate individual will appear just opposite leader being least and ears kept back,

presented by Granli, Poole (2006).

Chemical Interaction

A chemical interaction is also one of the important interactions in the elephant; it is an

energetically competent process and involves secretion of chemical signals which are

long lasting. They produce a wide odor signal and these odors are passed by the secretion

from different sources like reproductive tract, skin glands, face and expired air.

Figure 4.4 Temporal gland secretions

Sequential glands also produce secretion, a multi-lobed sac that secrets a strong

smelling liquid which is viscous between the eye and the ear (see Fig: 4.4). These

secretions occur when the elephant is in excited mood or under stress and secretion occur

in large quantity which denotes that gland is under automatic control, which is stated by


8

Wilson (2000).Signals which contains odor are sensed by the fellow individual and used

in communicative functions like individual recognition, alarm or trial making, these

signal are received by the Chemo-Receptors in the individual.

Elephants have highly developed odor sensing system which gives them acute sense of

smell and makes them to understand the chemical signal and transfer them to message.

It is seen that the elephants can differentiate between the human neighbors and the

unfamiliar ones. The African elephants that are located at Kenya's Amboseli National

Park do not react to the odor or color of the human garments but suddenly reacts

aggressively to the odor and color of the clothing of Masai Warriors, presented by

McKenna (2007).

Thus this illustrates that different racial groups must have diverse risks to the elephants as

they can learn by association.

To determine the reproductive state of the individuals elephants use chemical

interaction. Musth males have generally high level of testosterone and due to this they

secrete fluid from temporal gland and preferred by females and they also drip urine that

contains a powerful smell which can be detected by females.

Musth males have great physical condition, stated by Wyatt (2003) and are dominant

when compared to others so females generally prefer them for mating. Both Asian

(Elephas maximus) and African elephants follow this strategy, which is presented by

Rasmusser, Schulte (1998).


9

Tactile Interaction

Fig 4.5 Using trunk to pull vegetation off tall tree

Elephants also use touching as the form of interaction between them through

trunks and this is known as tactile interaction. Trunks in the elephants are used for

various functions like drinking, smelling, ripping vegetation from trees (sees Fig: 4.5),

but for tactile sense more importantly.

They use their trunks to investigate new territories, objects and exchanging the

touches with unfamiliar ones passing in the bush, in regard to the reproduction process

they communicate by intertwining their trunks with one another.

Feet are also a vital part of their tactile sense since they have soft skin, they can

sense the seismic vibration produced by the other elephants through ground using their

feet. The inner part of their feet are filled with Pacinian corpuscles, sensing elements

which senses the vibration are layered and covered with slimy gel. Vibration are

transferred to brain through these layers resulted in a nerve signal.

Their trunks also contain the vibration sensing elements, presented by Braden (2003) and

used in the same fashion as their feet by simply laying them to the ground.


10

Memory and Recognition

Due to the society in which they live elephants need a good memory and sharp

recognition capabilities. This is because they keep separated from the family on a regular

basis and at the same time they meet with other individuals from family and non-family

on a regular basis. So, they must recognize the kin from the non-kin; two individuals who

were separated for 23 years reunited after 23 years and are witnessed by Carol Buckley,

presented by Braden (2003).

Fig 4.6 Elephant reflection

Elephants have normally large brain and a highly developed cerebral cortex which

makes them enables to achieve a great potential to learn and retain such information for

longer duration of time, stated by Granli, Poole (2006).

Thus the elephants have a greater level of intelligence when compared to other

land mammals. Elephants have also a unique quality that only humans and some other


11

primitives poses, they can see their images in mirror and able to recognize it (see Fig

4.6).

The vital section of detection and memory in elephants is to keep away from

inbreeding despair from happening. Elephants are able to differentiate between parental

kin from non-kin using a phenotype similar to their smelling sense, but the mechanism is

still unknown.

The spreading of single-sex in males is incredibly a lot of necessary in preventing the

inbreed depression with addition to the capability that considers their kin and eliminate

postponing the period for dating within their group, presented by Moore (2007).

Elephants have very high sense of smelling they just can keep track of the family

members by simply smelling their urine and it allows them to create mental maps of their

co-specifics position, described by McKenna (2007).

During one revision given over African elephants exhibits that with urine samples

that were either of kin or alternative individual, positioned in a particular area that was

foreseeable or by unexpectedly. Elephant’s movement’s, characters and response to such

cues illustrated that they could distinguish up to 30 family members and 17 females.

Not only their sense provides recognition and great memory bur the family unit

also teaches the young kin in the family. The smaller kin watch their elder ones especially

mothers and sisters, learn from them how to find water, food. They use their trunk and

dig it into ground to find the water.

They also note the reaction of the adult and their behavior regarding different

individuals. During their adulthood they keep their information as a guide. They

generally lean mostly in their childhood which shows that they have got good memories.

It can be concluded from the above presented features we come to know that due

to their very advance sensing system elephants are the exceptionally sharp mammals.


12

Their social organization will not be as broad as today with regard to their interaction if

they don’t have the powerful sensing system of touch, smell, etc. they also learn by

interacting with the different individuals and have capacity to learn and recognize vital

cues for a large time period which adds to their intellect and social organization.

Based on the evolutionary characteristics of elephant, here in this research work,

the author has proposed a cross-layered design for optimizing the lifespan of wireless

networks (WSNs).

The overall system design has been presented in the following section:

4.4 Elephant Swarm Optimization for WSN-A Cross-Layer

Mechanism

In this section of the paper the system modeling adopted to realize the elephant

swarm optimization for wireless sensor networks is discussed.

Let us consider a wireless sensor nodes represented by a set which constitute

a static network defined as

{ }

In the considered network , the wireless interaction links that exist between two

nodes and , a relatively high transmission power allocation scheme is

considered. The high power allocation scheme causes the higher power utilization that

ultimately results into numerous interferences situation between other nodes as well as

degraded network life time and hence poor efficiency. The interaction channel being

considered over the links is nothing but Additive White Gaussian Noise ( ) channel

having confined noise power level. Here, one more factor called deterministic path loss

model has been assumed. If the signal to noise ratio of ainteraction link is

represented by then the maximum data rate supported per unit bandwidth is

defined as

( )


13

Where

This considered model can be realized using modulation schemes like .

The constellation size for the is and varies with time over a considered link,

stated by Leung, Sung (2006). The model assumes a scheduling system of

interaction between the nodes. The model considered assumes that there exists time

slots for the medium access control layer ( ) and a unique transmission mode is

applicable per slot.

Let us consider that a particular node transmits at a power level then the

power utilization of the amplifier is defined as

Where is the efficiency of power amplifier and to achieve the desired

signaling amplification, we need to consider some category of network models.

A homogenous sensor network model is consider to achieve for desired signal

amplification, .

The directed graph that represents the network under consideration, is defined as

Where indicates set of directed links.

Let | | | | indicates the incidence matrix of the graph then we can state that

{

}

We present an expression


14

Such that and and have the entries of 0 and 1.

As discussed earlier is the number of time slots in individual frame of the periodic

schedule. Represents the set of link scheduled. These are allowed to transmit during

time slot defined as

{ }

and

represents the power of transmission and per unit bandwidth rate

respectively over link and slot . The vectors of the time slot are and

| |. is the maximum limit of allowable transmission power for the node which

belongs to link . The analogous vector is | | The vectors id defined

as

( )

{

}

Where is the row of the matrices . Also (

)

| |

The vector is defined as

( )

{

}

Where is the row of the matrices . Also (

)

| |

The initial homogenous energy of every node defined as

and the energy | |

Let represents power utilization of transmitter and represents the power

utilization of the receiver and is assumed to be homogenous for every nodes. The

consumed by each node is


15

Let the sensing events that are induced in the network induce an information

generation rate represented as . It can be stated that | | represents a vector

which constitute of .

The data aggregated at the sink is defined as

∑

The link gain matrix of the wireless sensor network considered is defined as

| | | |

The power from the transmitter of the link to the receiving node on link is

represented as and represents the total noise power over the operational

bandwidth.

The represent the network lifespan when a percentage of nodes runs out of

energy. This is a common criterion considered by researchers to evaluate their proposed

algorithms, presented by International Standard – ISO/IEC (1996), Tanenbaum (2003).

The maximum data rate supported for transmission over a particular Link is defined

as

( )

4.5 Problem Formulation

A cross-layer approach is adopted to enhance the network lifespan of the wireless

sensor network. Elephants are social animals and are said to possess strong memory of

the events that occur.

The problem of optimizing or maximizing the life span of the network can be presented

as a function defined as follows


16

(

∑

)

The maximization function can be defined as

∑ (

)

For all time slots and , the constituting variables are

,

,

, for a set { } .

Let us define a variable such that

The elephant swarm optimization is used to attain minimized function defined as

(

∑

)

The minimization function or the elephant swarm optimization objective can be

defined as

∑ (

)

The model presented here considers based systems the minimization

function can be defined as


17

∑ ∑

(

)

∑

(

) ∑

∑

{ }

Where represents the link, the number of slots assigned on is . is the set

of transmitting links and is the receiving links of the sensor node . The

variable is defined as follows

And is defined as

The transmission power the link represented as is defined as

It must be noticed that the power of transmission over a network link is presented as


18

4.6 Cross-Layer Optimization to realize Elephant Swarm

Behavior

The presented section of this work elaborates the elephant swarm optimization

algorithm for routing, scheduling and advanced radio layer control

techniques. The elephant swam optimization is used taking into account unconstrained

scheduling on the network links. The elephant swarm optimization enables simultaneous

scheduling of the sensing data on the interfering wireless interaction links in the

current considered scheduling time slot. The elephant swarm optimization iterates to

obtain an optimal routing, power utilization and schedule to enhance the

considered network lifespan. The elephant model is adopted to solve optimization

objective defined in the former section of this research work.

Let us consider a link schedule of data defined as where { }.

The rate of transmission that can be supported over a link can be expresses as based

on approximations is defined as

(

∑

)

If the of a link is then the minimum transmission rate is defined as

following

.

The elephant swarm optimization results arising based on the above approximations for

are said to be a part of the function optimization set.

Let us define a variable (

)

Then the above equation for the maximum transmission rate optimization

can be

defined as can be


19

(

∑

)

Based on the above arguments the elephant swarm optimization objective can

be expressed as

(

∑

)

∑ ( ∑ (

)

∑

)

The above defined elephant swarm optimization is applicable provided

and { }

In other terms the elephant swarm optimization is applicable if the links have a

greater than unity.

The scheduling over every links is not adopted as the power

utilization would exponentially increase. The elephant swarm optimization is used on

every links scheduled . The computational complexity of optimization under

such circumstances can be defined as

From the above equation it is evident that the optimization is

computationally heavy and increases exponentially as the links of the sensor nodes

increase (i.e. for dense networks) and the slot value increases. The computation

complexity of the elephant swarm optimization can be reduced if the number of TDMA-


20

MAC slots is doubled to . The two fold increase in the number of time slots enables

achieving lower power utilization as the sensor nodes have numerous slot options and

sleep induction is effective. Furthermore in the case of high sensing activity leading to

greater data transmissions, the data to the sink is scheduled using multiple TDMA slots to

enable energy conservation and accurate data aggregation.

The elephant swarm optimization model can be summarized in the form of the algorithm

given below realized through multiple phases described below.

Phase A:

Initialize the schedule based on the data . The is initialized such that

link . the schedule is constructed in a manner such that every

links are provided at least a slot in

Phase B:

In this section the following equation is solved

∑ ( ∑ (

)

∑

)

If the results obtained on solving are not suitable then the

optimization is not possible. If the solutions satisfy the condition then

elephant swarm route optimization and radio layer optimizations are carried out to

support the required transmission rate.

Phase C:

Evaluate every links and retain the links if the following equation is satisfied.

∑


21

This section eliminates every links whose is less than unity and retaining the links

having an acceptable .

Phase D:

Compute using the following equation

( ∑ (

)

)

Compute defined as

( ∑

)

Using the above definitions we can obtain the new the layer

schedule represented as and . If the optimized schedule is

equitant to the existing or previous schedule then no further optimization is possible. If

the optimized is not similar to the current and previous MAC layer schedule the new

schedule is adopted. Enables to identify the maximum power utilization link so that

it can be scheduled it the additional slots available and thus achieving energy

conservation.

Phase E:

In the last section of the elephant swarm optimization algorithm the optimal

solution achieved using a cross-layer approach is verified using the following definition

(

∑

) { }

If the solution does not satisfy the above equation then no optimization is possible

owing to current network dependent reasons. If optimal solution is obtained and


22

incorporated network performance in terms of data aggregation, improved data rates and

higher network lifespan.

The elephant swarm optimization is realized using a cross-layer design approach

to enhance network lifespan. The efficiency and the performance measure of this

optimization technique are discussed in the subsequent section of this thesis.

elephant swarm optimization in wireless sensor...

Documents