IoMT-Cloud Task Scheduling Using AI

作     者：Adedoyin A.Hussain Fadi Al-Turjman 

作者机构：Computer Engineering Department and Research Centre for AI and IoTNear East UniversityNicosiaTurkey Computer Engineering DepartmentCyprusWest UniversityGazimagusaTurkey Artificial Intelligence Engineering Department and AI and Robotics InstitutesNear East UniversityNicosiaTurkey Research Centre for AI and IoTFaculty of EngineeringUniversity of KyreniaKyreniaTurkey 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2023年第135卷第5期

页      面：1345-1369页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Artificial intelligence IoMT hybrid genetic algorithm cloud 

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