Affiliations: [a] Department of Electronics and Communication Engineering, National Institute of Technology Silchar, India
| [b] Department of Computer Science and Engineering, Guru Nanak Dev University, Regional Campus, Gurdaspur, Punjab, India
Correspondence:
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Corresponding author. A. Majumdar, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, India. E-mail: [email protected].
Abstract: With the advent of IoT, cloud/fog based healthcare systems have become a growing trend in modern healthcare systems. These systems comprise of smart sensors, which on integration with medical devices, generate heterogeneous medical big data that can be used in diagnosis of various diseases. However, there is a continuous flow of large quantity of data in such a systems, due to which it may face many difficulties. Among various pre-requisites for proper functioning of these systems, lifetime is a vital factor. Keeping in view these aspects, the use of new hybrid whale-PSO algorithm (HWPSO) in clustering has been proposed for prolonging the network lifetime by preserving the power of network edge devices. In addition to this, a novel fitness function with a set of relevant criteria of edge devices such as energy factor, average intra-cluster distance, average distance to cluster leader over data analytics center, average sleeping time, and computational load has been taken into account in the selection of cluster leader. The cluster leader is responsible for managing intra-cluster and inter-cluster data communication.
Keywords: e-Healthcare, fog computing, particle swarm optimization, whale optimization
