Machine Learning-Enabled Communication Approach for the Internet of Medical Things

作     者：Rahim Khan Abdullah Ghani Samia Allaoua Chelloug Mohammed Amin Aamir Saeed Jason Teo 

作者机构：Faculty of Computing and InformaticsUniversity Malaysia SabahKota KinabaluSabah88400Malaysia Department of Information TechnologyCollege of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box84428Riyadh11671Saudi Arabia Department of Computer ScienceAbdul Wali Khan UniversityMardan23200Pakistan College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science and ITUET PeshawarJalozai CampusJalozai24240Pakistan 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第76卷第8期

页      面：1569-1584页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 12[管理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 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] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0835[工学-软件工程] 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）] 

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023R239) Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia 

主　　题：Machine learning Internet of Medical Things healthcare load balancing communication 

摘      要：The Internet ofMedical Things(IoMT)is mainly concernedwith the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically,whereas machine learning approaches enable these smart systems to make informed ***,broadcasting is used for the transmission of frames,whereas congestion,energy efficiency,and excessive load are among the common issues associated with existing *** this paper,a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames,especially with the minimum possible communication overheads in the IoMT *** this purpose,the proposed scheme utilises a well-known technique,i.e.,Kruskal’s algorithm,to find an optimal path from source to destination wearable ***,other evaluation metrics are used to find a reliable and shortest possible communication path between the two interested *** from that,every device is bound to hold a supplementary path,preferably a second optimised path,for situations where the current communication path is no longer available,either due to device failure or heavy ***,the machine learning approach helps enable these devices to update their routing tables simultaneously,and an optimal path could be replaced if a better one is *** proposed mechanism has been tested using a smart environment developed for the healthcare domain using IoMT *** results show that the proposed machine learning-oriented approach performs better than existing approaches where the proposed scheme has achieved the minimum possible ratios,i.e.,17%and 23%,in terms of end to end delay and packet losses,***,the proposed scheme has achieved an approximately 21%improvement in the average throughput compared to the existing schemes.