[Retracted] A Neighborhood and Machine Learning-Enabled Information Fusion Approach for the WSNs and Internet of Medical Things

Table 2

A detailed comparative analysis of the proposed and existing state-of-the-art schemes.

Schemes	Data aggregation	Energy consumption (J)	End-to-end delay (ms)	Normalized overhead	PDR (%)	Throughput (Mbps)	Dead nodes
NCDAS	70.23%	6.55	1.532	1.001	93.22	66.26	16
Proposed with SVM	45.28%	8.54	1.87	1.015	90.21	63.22	23
Proposed with k-mean	66.23%	8.1	2.92	1.19	87.21	64.22	35
IDK	69.56%	8.678	3.41	1.45	68.58	63.84	33
SVM	55.56%	9.1	2.11	1.35	87.11	53.91	51
Euclidean distance	56.24%	8.92	2.96	1.16	86.24	60.84	42
Cosine distance	57.6%	8.76	1.96	1.56	65.15	42.01	38