Enhancing Firefly Algorithm for better Network lifetime optimization in Healthcare Monitoring System - Cloud Computing Environment

Abstract

The Internet of Things (IoT), a new phenomenon in the technology industry, is mostly responsible for updating healthcare systems by gathering and analyzing patient physiological data through wearable technology and sensor networks. It is difficult to process so much data from so many IoT devices in such a short amount of time. Maximizing the network lifetime is one of the most significant tasks faced by any wireless sensor network. The objective of the study described in this paper was to apply swarm intelligence metaheuristics to optimize the cluster head selection. In order to extend the lifetime of the WSN, we have implemented both the original firefly algorithm (FA) and the proposal for the revised FA. Additionally, According to the proposed study, sensitive data is created and stored by IoT devices, which are vulnerable to attack, and data processing is handled by the edge server. Standard security algorithms like AES, DES, and RSA make it difficult for the majority of IoT devices to function successfully because of their restricted resources. For real-time processing, visualization, and diagnosis, the real-time data is subsequently sent to a distant cloud server.