how I can find the central point in randomly distributed WSN and how I can get the nearest sensor node for this point?

y_cor = 100

x_cor = 100

n = 10

I need to find the nearest node for the central and defined it as a Cluster Head.

All Thanks;

Answer 1

[Image Analyst]

To find the x and y closest to the mean/centroid in a set of (x,y) coordinates you can do (untested)

meanx = mean(x);
meany = mean(y);
distances = sqrt((x - meanx) .^ 2 + (y - meany) .^ 2);
% Find the distance that is closest to the means.
[minDistance, indexOfMin] = min(distances);
xClosestToCentroid = x(indexOfMin);
yClosestToCentroid = y(indexOfMin);

[Momen AlManaseh]

please, can you declare the parameters?

[Image Analyst]

What parameters? There are none. All there is are the x and y coordinates, which presumably you already have. If you don't have your x and y, then there is no need or ability to find the centroid or the point closest to the centroid.

[Momen AlManaseh]

i ask about mean() function, in my case this function return the same value of x & y .

[Image Analyst]

The mean() function is a built-in function. It will only return the same value if the means are the same. What does this show for you

m1 = mean([1,2,3])
m2 = mean([7,8,9])

You should see

m1 =

2

m2 =

8

so m1 and m2 should not be the same.

[Momen AlManaseh]

Ok

thank you so much

[Momen AlManaseh]

excuse, I have last question about

[minDistance, indexOfMin] = min(distances);

[Image Analyst]

When you read the documentation you saw this:

https://www.mathworks.com/help/releases/R2021a/matlab/ref/min.html?doclanguage=en&prodfilter=ML+VP+DB+NN+IA+IP+CO+DM+SG+ST&addons=usbwebcams#d123e857080

[M,I] = min(A,[],___,'linear') returns the linear index into A that corresponds to the minimum value in A.

So now, what is your last question? You didn't actually ask any question.

[Momen AlManaseh]

I want to ask how I can find the distances between the center node and all the other nodes?

[Image Analyst]

@Momen AlManaseh, since I did this

distances = sqrt((x - meanx) .^ 2 + (y - meany) .^ 2);

distances is the distances of all nodes to the centroid. If you want the distances from all the nodes to the node that is closest to the centroid (and may not be exactly at the centroid), then you can use the location of that node instead of meanx and meany:

distances = sqrt((x - xClosestToCentroid) .^ 2 + (y - yClosestToCentroid ) .^ 2);

[Momen AlManaseh]

Thanks for your time

best regards