Algorithm 3: Parametric approach for the balanced cluster structure

Input:

X = consists of a total n number of data items.

Copt = optimal clusters density

Ethreshold = energy threshold

Output:

A complete set of Copt clusters.

Steps:

1: Find Copt initial CHs by using Algorithms 1 and 2.

2: Repeat

3: Rest of SNs join the nearest CH based on Euclidean distance.

4: Centroid for each cluster:

Centroid (x,y) = $\left(\frac{1}{S} {\displaystyle \sum }_{i=1}^S{x}_i, \frac{1}{S} {\displaystyle \sum }_{i=1}^S{y}_i\right)$

5: Once optimum cluster is formed, all SNs are assigned IDs based on the distance from centroid. Closer SNs will be assigned small numbers.

6. For all selected CHs

7:    if CH residual energy ≥ Ethreshold

8:     then

9:        CH won’t change

10:   else

11:       SNs ID numbers will be checked in the cluster

12:       SN having next ID number is elected as a new CH.

13: End If

14: End for

15: Beacon signal will be send to all SNs to inform them about the change of new CH.

16: Until The CH residual energy meets the threshold level and no change in the CH anymore.