摘要
The internet of medical things(IoMT)empowers patients to get adaptable,and virtualized gear over the internet.Task scheduling is the most fundamental problem in the IoMT-cloud since cloud execution commonly relies on it.Thus,a proposition is being made for a distinct scheduling technique to suitably meet these solicitations.To manage the scheduling issue,an artificial intelligence(AI)method known as a hybrid genetic algorithm(HGA)is proposed.The proposed AI method will be justified by contrasting it with other traditional optimization and AI scheduling approaches.The CloudSim is utilized to quantify its effect on various parameters like time,resource utilization,cost,and throughput.The proposed AI technique enhanced the viability of task scheduling with a better execution rate of 32.47ms and a reduced time of 40.16ms.Thus,the experimented outcomes show that the HGA reduces cost as well as time profoundly.
