The Internet of Medical Things (IoMT) has numerous prospective applications for remote health monitoring in the medical field. The two main issues that significantly affect IoMT’s performance are end-to-end latency and energy efficiency. An energy-efficient architecture and reliable packet communication are necessary for design and implementation of an application. It is very crucial to transmit accurate packet with real time and reliable manner. A cluster-based and energy-efficient routing protocol using the Blockchain-enabled joint trust (FG-WHO-BWOA) method in IoMT has been presented to address these problems. It finds the network’s optimal cluster head (CH) and ensures secure packet communication. Here, the firefly and grey wolf optimization (FG-WHO) technique is applied to precisely pick CH. The vulnerable or malicious node appears in a cluster following the selection of CH. In order to identify the trusted path among the various routes, the multi-objective Beluga Whale Optimization Algorithm (BWOA) is suggested. Finally, the block chain receives the optimal chosen trust channels for safer and more reliable network transmission. Castalia Simulator is used to perform the simulation. High throughput, high efficiency, long network lifetime, high packet delivery ratio, low latency, low consumption of energy, low packet loss ratio and security are all attained by the suggested FG-WHO-BWOA. The performance validates that, in contrast to the current approaches, the mentioned strategy performs better.
Sunayana Das, Tusharkanta Samal, N. R. Samal et al.· Scientific Reports· 0 citations
This paper presents a comprehensive performance analysis of a solar photovoltaic (PV) and battery-based bipolar microgrid system under various conditions. The system is designed to enhance reliability, efficiency, and power quality in modern energy networks. The proposed system consists of a PV system with a boost converter, a battery system with a bidirectional DC–DC converter, and a three phase neutral point clamped inverter. The system was modeled and simulated in MATLAB/Simulink software to evaluate the system under multiple operating scenarios: (i) constant solar irradiance with varying load conditions, (ii) varying solar irradiance with varying load, and (iii) varying solar irradiance under constant load conditions. A dual loop proportional-integral controller-based strategy was implemented to regulate the converters, maintaining DC-link voltage and grid frequency. The simulation results show that the system demonstrates effective adaptation to sudden changes in various conditions, maintaining power quality. The results show that the proposed bipolar microgrid architecture helps to coordinate the system to maintain stable DC-link voltage and achieve balanced power distribution, and ensure smooth battery charging and discharging under dynamic operating conditions.
