M. DHIVYA ET AL.

252

problem-solving process in Multi agent system (MAS)

into kinematics and dynamics of particles in the for-

ceield.When all the particles reach their equilibrium

states, the solution to the optimization of task allocation

and resource assignment is obtained.

4. Cuckoo Based Particle Approach (CBPA)

The energy function for the Cuckoo Search is designed

as [17];

1

1

100*

n

i

dfi di

(6)

The above equation is derived from Equation (2), by

considering the value of εmp as 100 pJ/bit/m2 for n = 2,

i.e.; communication range between the sensors. The fit-

ness function F, is considered in this problem for mini-

mization of energy and maximization of lifetime of the

nodes.

4.1. Proposed Algorithm for Data Fusion

Input: A set of N sensor nodes in randomly deployed

field and a base station.

Step 1: Initialization:

Select the number of sensor nodes, cuckoo nests, eggs

in nests to start the search. Initialize the location and en-

ergy of nodes and the location of base station.

Step 2: Formation of Static Clusters:

The clusters are formed, by Cuckoo Search technique.

Each egg in a nest corresponds to a sensor node. A group

of M nests are chosen with N eggs in it. The probability

of choosing the best egg or quality egg is done by random

walk. Step size and Levy angle is updated in each itera-

tion. In turn the nests are updated. The optimal solution

i.e.; best egg – high energy node is taken as cluster head

in context to energy, distance between the nodes and dis-

tance to the base station.

The worse nets are abandoned in normal Cuckoo

Search. In order to compensate the unequal energy dissi-

pation, the worse nets (or) least energy nodes are allowed

to join the cluster as non cluster head nodes, in the pro-

posed approach. The less energy nodes join the proximity

cluster heads to form cluster. The cluster formation is

done by appropriate advertisement of cluster-head to all

other nodes to join a particular cluster. The cluster head is

not permanent. In each run, according to the residual en-

ergy of the nodes, the cluster head is periodically changed.

This helps to eradicate the communication overhead and

redundancy.

Step 3: Shortest Path Routing:

After the clusters are formed, the Cluster Heads (CHs)

fuse or aggregate the information before forwarding it to

the base station. The energy model incorporates free

space radio model followed by all nodes. The inter cluster

and intra cluster routing via shortest path is to be per-

formed based on the application. Intra cluster refers to

communication between cluster-head and non cluster-

head nodes within the cluster. Inter cluster communica-

tion refers to communication between the clusters. For

intra cluster communication, the most widely used meth-

odology as followed by the basic LEACH algorithm con-

cept is TDMA Scheduling- Time Division Multiple Ac-

cess Scheduling is followed.

For inter cluster communication, Generalized Particle

Model is used. The objective of using GPM approach is

optimization of route and extension of the network life-

time. GPM is given in many types according to the net-

work optimization problems by Dianxun Shuai. Normally,

communication between two Wireless Sensor Nodes

happens, when there is no other interfering node between

two nodes. It is assumed that there exists wireless path

and link between two nodes during communication.

The Generalized Particle Model transforms the net-

work shortest path problem into kinematics and dynamics

of numerous particles in a force-field. Nodes are consid-

ered as particles, and utility, overall utility, potential en-

ergy due to gravitational force, potential energy due to

interactive force of particles are calculated in each itera-

tion. It is personified in the described model, as the resul-

tant forces on the particles are high, the particles also

move fast. Then the particles are tested for stability con-

dition. If the particles are stable, then the algorithm is

terminated successfully. Else the particles are updated,

with the hybrid energy equations to obtain the optimal

solution.

The shortest path is calculated by the link cost of each

links. The link cost is substituted as the residual energy of

nodes; with context to the distance to the communicating

nodes. In more brief terms the residual energy of cluster

head to communicating cluster head is to be considered

for communication of the sensed data. After several

numbers of iterations, the optimal path to transmit the

data to the base station is being established.

The important steps in Cuckoo Based Particle Ap-

proach (CBPA) are listed in Figure 4.

5. Results and Analysis

In this section the performance of the proposed technique

is evaluated via simulation results. The network model is

simulated using MATLAB. The results are summarized

after running several iterations.

The focus on this paper, as by the objective function, is

minimization of energy and maximization of lifetime.

The simulation Parameters are listed in Table 1.

Copyright © 2011 SciRes. IJCNS