A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization

Algorithm 1

Principal component analysis for dimensionality reduction [23].

	module PCA(Z)
(i)	Compute sample mean and sample covariance matrix:
(ii)	Compute eigen values and eigen vectors of
(iii)	Formulate transformation matrix S = [t1, t2,……..ty] with y eigen vectors in association with y largest eigen values.
(iv)	Now, do the projection of overall data Z into the subspace of PCA such as:
(v)	Return r
	End module