The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We pro...The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.展开更多
Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network pro...Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.展开更多
In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management...In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.展开更多
基金This research was supported by Science and Technology Research Project of Education Department of Jiangxi Province,China(Nos.GJJ2206701,GJJ2206717).
文摘The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.
文摘Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission range.It is depicted as significant research challenges that pose during the design of network protocol in wireless networks.Based on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are unidirectional.It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message.Therefore,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric links.It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation.Here,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and delay.For the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is evaluated.The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity.This learning model is a productive way for resolving the routing issues over the network model during uncertainty.The asymmetric path is chosen to achieve exploitation and exploration iteratively.The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem.Here,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)model.The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others.The average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.
基金This work was supported by the National Natural Science Foundation of China(61772196,61472136)the Hunan Provincial Focus Social Science Fund(2016ZDB006)+2 种基金Hunan Provincial Social Science Achievement Review Committee results appraisal identification project(Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee(XSP 19ZD1005)The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology(2017TP1026).
文摘In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.
