In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in ...In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.展开更多
In this article,we introduce a new bi-directional dual-relay selection strategy with its bit error rate(BER)performance analysis.During the first step of the proposed strategy,two relays out of a set of N relay-nodes ...In this article,we introduce a new bi-directional dual-relay selection strategy with its bit error rate(BER)performance analysis.During the first step of the proposed strategy,two relays out of a set of N relay-nodes are selected in a way to optimize the system performance in terms of BER,based on the suggested algorithm which checks if the selected relays using the maxmin criterion are the best ones.In the second step,the chosen relay-nodes perform an orthogonal space-time coding scheme using the two-phase relaying protocol to establish a bi-directional communication between the communicating terminals,leading to a significant improvement in the achievable coding and diversity gain.To further improve the overall system performance,the selected relay-nodes apply also a digital network coding scheme.Furthermore,this paper discusses the analytical approximation of the BER performance of the proposed strategy,where we prove that the analytical results match almost perfectly the simulated ones.Finally,our simulation results show that the proposed strategy outperforms the current state-of-the-art ones.展开更多
Rotman lens,which is a radio frequency beam-former that consists of multiple input and multiple output beam ports,can be used in industrial,scientific,and medical applications as a beam steering device.The input ports...Rotman lens,which is a radio frequency beam-former that consists of multiple input and multiple output beam ports,can be used in industrial,scientific,and medical applications as a beam steering device.The input ports collect the signals to be propagated through the lens cavity toward the output ports before being transmitted by the antenna arrays to the destination in order to enhance the error performance by optimizing the overall signal to noise ratio(SNR).In this article,a low-cost Rotman lens antenna is designed and deployed to enhance the overall performance of the conventional cooperative communication systems without needing any additional power,extra time or frequency slots.In the suggested system,the smart Rotman lens antennas generate a beam steering in the direction of the destination to maximize the received SNR at the destination by applying the proposed optimal beamforming technique.The suggested optimal beamforming technique enjoys high diversity,as well as,low encoding and decoding complexity.Furthermore,we proved the advantages of our suggested strategy through both theoretical results and simulations using Monte Carlo runs.The Monte Carlo simulations show that the suggested strategy enjoys better error performance compared to the current state-of-the-art distributed multiantenna strategies.In addition,the bit error rate(BER)curves drawn from the analytical results are closely matching to those drawn from our conducted Monte Carlo simulations.展开更多
The differential equations having delays take paramount interest in the research community due to their fundamental role to interpret and analyze the mathematical models arising in biological studies.This study deals ...The differential equations having delays take paramount interest in the research community due to their fundamental role to interpret and analyze the mathematical models arising in biological studies.This study deals with the exploitation of knack of artificial intelligence-based computing paradigm for numerical treatment of the functional delay differential systems that portray the dynamics of the nonlinear influenza-A epidemic model(IA-EM)by implementation of neural network backpropagation with Levenberg-Marquardt scheme(NNBLMS).The nonlinear IA-EM represented four classes of the population dynamics including susceptible,exposed,infectious and recovered individuals.The referenced datasets for NNBLMS are assembled by employing the Adams method for sufficient large number of scenarios of nonlinear IA-EM through the variation in the infection,turnover,disease associated death and recovery rates.The arbitrary selection of training,testing as well as validation samples of dataset are utilizing by designed NNBLMS to calculate the approximate numerical solutions of the nonlinear IA-EM develop a good agreement with the reference results.The proficiency,reliability and accuracy of the designed NNBLMS are further substantiated via exhaustive simulations-based outcomes in terms of mean square error,regression index and error histogram studies.展开更多
基金This research was supported in part by the National Natural Science Foundation of China under Grant No.62062031 and 61877053in part by Inner Mongolia natural science foundation grant number 2019MS06035,and Inner Mongolia Science and Technology Major Project,China+1 种基金in part by ROIS NII Open Collaborative Research 21S0601in part by JSPS KAKENHI grant numbers 18KK0279,19H04093,20H00592,and 21H03424.
文摘In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.
基金This work was supported by College of Engineering and Technology,the American University of the Middle East,Kuwait.Homepage:https://www.aum.edu.kw.
文摘In this article,we introduce a new bi-directional dual-relay selection strategy with its bit error rate(BER)performance analysis.During the first step of the proposed strategy,two relays out of a set of N relay-nodes are selected in a way to optimize the system performance in terms of BER,based on the suggested algorithm which checks if the selected relays using the maxmin criterion are the best ones.In the second step,the chosen relay-nodes perform an orthogonal space-time coding scheme using the two-phase relaying protocol to establish a bi-directional communication between the communicating terminals,leading to a significant improvement in the achievable coding and diversity gain.To further improve the overall system performance,the selected relay-nodes apply also a digital network coding scheme.Furthermore,this paper discusses the analytical approximation of the BER performance of the proposed strategy,where we prove that the analytical results match almost perfectly the simulated ones.Finally,our simulation results show that the proposed strategy outperforms the current state-of-the-art ones.
基金The article has been supported by the College of Engineering and Technology,American University of the Middle East,Kuwait.Homepage:https://www.aum.edu.kw.
文摘Rotman lens,which is a radio frequency beam-former that consists of multiple input and multiple output beam ports,can be used in industrial,scientific,and medical applications as a beam steering device.The input ports collect the signals to be propagated through the lens cavity toward the output ports before being transmitted by the antenna arrays to the destination in order to enhance the error performance by optimizing the overall signal to noise ratio(SNR).In this article,a low-cost Rotman lens antenna is designed and deployed to enhance the overall performance of the conventional cooperative communication systems without needing any additional power,extra time or frequency slots.In the suggested system,the smart Rotman lens antennas generate a beam steering in the direction of the destination to maximize the received SNR at the destination by applying the proposed optimal beamforming technique.The suggested optimal beamforming technique enjoys high diversity,as well as,low encoding and decoding complexity.Furthermore,we proved the advantages of our suggested strategy through both theoretical results and simulations using Monte Carlo runs.The Monte Carlo simulations show that the suggested strategy enjoys better error performance compared to the current state-of-the-art distributed multiantenna strategies.In addition,the bit error rate(BER)curves drawn from the analytical results are closely matching to those drawn from our conducted Monte Carlo simulations.
文摘The differential equations having delays take paramount interest in the research community due to their fundamental role to interpret and analyze the mathematical models arising in biological studies.This study deals with the exploitation of knack of artificial intelligence-based computing paradigm for numerical treatment of the functional delay differential systems that portray the dynamics of the nonlinear influenza-A epidemic model(IA-EM)by implementation of neural network backpropagation with Levenberg-Marquardt scheme(NNBLMS).The nonlinear IA-EM represented four classes of the population dynamics including susceptible,exposed,infectious and recovered individuals.The referenced datasets for NNBLMS are assembled by employing the Adams method for sufficient large number of scenarios of nonlinear IA-EM through the variation in the infection,turnover,disease associated death and recovery rates.The arbitrary selection of training,testing as well as validation samples of dataset are utilizing by designed NNBLMS to calculate the approximate numerical solutions of the nonlinear IA-EM develop a good agreement with the reference results.The proficiency,reliability and accuracy of the designed NNBLMS are further substantiated via exhaustive simulations-based outcomes in terms of mean square error,regression index and error histogram studies.
