An effective communication and computation model based on a hybridgraph-deeplearning approach for SIoT

作     者：M.S.Mekala Gautam Srivastava Ju H.Park Ho-Youl Jung M.S.Mekala;Gautam Srivastava;Ju H.Park;Ho-Youl Jung

作者机构：Department of Information and Communication EngineeringYeungnam UniversityGyeongsan38544South Korea RLRC LAb for Autonomous Vehicle Parts and Materials InnovationYeungnam UniversityGyeongsan38544South Korea Department of Math and Computer ScienceBrandon UniversityBrandonCanada Department of Electrical EngineeringYeungnam UniversityGyeongsanSouth Korea Research Centre for Interneural ComputingChina Medical UniversityTaichungTaiwanChina 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2022年第8卷第6期

页      面：900-910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：supported in part by Basic Science Research Programs of the Ministry of Education(NRF-2018R1A2B6005105) in part by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2019R1A5A8080290) 

主　　题：Edge computing Adaptive trust weight(ATW)model Quotient user-centric coeval-learning(QUCL)mechanism Deep learning Service reliability 

摘      要：Social Edge Service(SES)is an emerging mechanism in the Social Internet of Things(SIoT)orchestration for effective user-centric reliable communication and *** services are affected by active and/or passive attacks such as replay attacks,message tampering because of sharing the same spectrum,as well as inadequate trust measurement methods among intelligent devices(roadside units,mobile edge devices,servers)during computing and *** issues lead to computation and communication overhead of servers and computation *** address this issue,we propose the HybridgrAph-Deep-learning(HAD)approach in two stages for secure communication and ***,the Adaptive Trust Weight(ATW)model with relation-based feedback fusion analysis to estimate the fitness-priority of every node based on directed graph theory to detect malicious nodes and reduce computation and communication ***,a Quotient User-centric Coeval-Learning(QUCL)mechanism to formulate secure channel selection,and Nash equilibrium method for optimizing the communication to share data over edge *** simulation results confirm that our proposed approach has achieved effective communication and computation performance,and enhanced Social Edge Services(SES)reliability than state-of-the-art approaches.