With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based on...With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based onUAV is urgently needed to avoid major safety accidents.At the same time,the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of devices.As a result,the Dispersed Computing(DCOMP)architecture enables collaborative computing between devices in the Internet of Everything(IoE),promotes low-latency and efficient cross-wide applications,and meets users’growing needs for computing performance and service quality.This paper focuses on examining the resource allocation challenge within a dispersed computing environment that utilizes UAV inspection tracks.Furthermore,the system takes into account both resource constraints and computational constraints and transforms the optimization problem into an energy minimization problem with computational constraints.The Markov Decision Process(MDP)model is employed to capture the connection between the dispersed computing resource allocation strategy and the system environment.Subsequently,a method based on Double Deep Q-Network(DDQN)is introduced to derive the optimal policy.Simultaneously,an experience replay mechanism is implemented to tackle the issue of increasing dimensionality.The experimental simulations validate the efficacy of the method across various scenarios.展开更多
Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its ...Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.展开更多
Dispersed computing can link all devices with computing capabilities on a global scale to form a fully decentralized network,which can make full use of idle computing resources.Realizing the overall resource allocatio...Dispersed computing can link all devices with computing capabilities on a global scale to form a fully decentralized network,which can make full use of idle computing resources.Realizing the overall resource allocation of the dispersed computing system is a significant challenge.In detail,by jointly managing the task requests of external users and the resource allocation of the internal system to achieve dynamic balance,the efficient and stable operation of the system can be guaranteed.In this paper,we first propose a task-resource joint management model,which quantifies the dynamic transformation relationship between the resources consumed by task requests and the resources occupied by the system in dispersed computing.Secondly,to avoid downtime caused by an overload of resources,we introduce intelligent control into the task-resource joint management model.The existence and stability of the positive periodic solution of the model can be obtained by theoretical analysis,which means that the stable operation of dispersed computing can be guaranteed through the intelligent feedback control strategy.Additionally,to improve the system utilization,the task-resource joint management model with bi-directional intelligent control is further explored.Setting control thresholds for the two resources not only reverse restrains the system resource overload,but also carries out positive incentive control when a large number of idle resources appear.The existence and stability of the positive periodic solution of the model are proved theoretically,that is,the model effectively avoids the two extreme cases and ensure the efficient and stable operation of the system.Finally,numerical simulation verifies the correctness and validity of the theoretical results.展开更多
With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)...With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points(NCPs).Considering the amount of task data and the idle resources of NCPs,a computing resource scheduling model for NCPs is established.Taking the heterogeneous task execution delay threshold as a constraint,the optimization problem is described as the problem of maximizing the utilization of computing resources by NCPs.The proposed problem is proven to be NP-hard by using the method of reduction to a 0-1 knapsack problem.A many-to-many matching algorithm based on resource preferences is proposed.The algorithm first establishes the mutual preference lists based on the adaptability of the task requirements and the resources provided by NCPs.This enables the filtering out of un-schedulable NCPs in the initial stage of matching,reducing the solution space dimension.To solve the matching problem between ICVs and NCPs,a new manyto-many matching algorithm is proposed to obtain a unique and stable optimal matching result.The simulation results demonstrate that the proposed scheme can improve the resource utilization of NCPs by an average of 9.6%compared to the reference scheme,and the total performance can be improved by up to 15.9%.展开更多
We investigate the elastic waves excited by an arbitrary plane piezoelectric source on the surface of a multilayered medium. Based on the previous studies, the 2D elastic wavefield in the multilayered medium is extend...We investigate the elastic waves excited by an arbitrary plane piezoelectric source on the surface of a multilayered medium. Based on the previous studies, the 2D elastic wavefield in the multilayered medium is extended to 3D space. The propagator matrix for the 3D wavefield is investigated and the displacement-stress response for the boundary conditions is obtained. The excitation and propagation of the Rayleigh and Love waves are analysed further. It is found that the propagation velocity of the Rayleigh and Love waves does not depend on the propagation azimuth θ in the plane parallel to the free surface of the multilayered medium while the displacement is strongly dependent on the azimuth θ.展开更多
In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approxima...In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approximate the high-order spatial differential operators and transform the seismic wave equations into semi-discrete ordinary differential equations （ODEs）. Then, the converted ODE system is solved by the exponential time difference （ETD） method. We investigate the properties of NETD in detail, including the stability condition for 1-D and 2-D cases, the theoretical and relative errors, the numerical dispersion relation for the 2-D acoustic case, and the computational efficiency. In order to further validate the method, we apply it to simulating acoustic/elastic wave propagation in mul- tilayer models which have strong contrasts and complex heterogeneous media, e.g., the SEG model and the Mar- mousi model. From our theoretical analyses and numerical results, the NETD can suppress numerical dispersion effectively by using the displacement and gradient to approximate the high-order spatial derivatives. In addition, because NETD is based on the structure of the Lie group method which preserves the quantitative properties of differential equations, it can achieve more accurate results than the classical methods.展开更多
The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computa...The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computational Fluid Dynamics（CFD） model. The boundary conditions of different PBL structures/conditions were provided by simulations of the Weather Researching and Forecasting model. The simulated results of the idealized 2D and 3D street canyon experiments showed that the increment of PBL instability favored the downward transport of momentum from the upper flow above the roof to the pedestrian level within the street canyon. As a result, the flow and turbulent fields within the street canyon under the more unstable PBL condition are stronger. Therefore, more pollutants within the street canyon would be removed by the stronger advection and turbulent diffusion processes under the unstable PBL condition. On the contrary, more pollutants would be concentrated in the street canyon under the stable PBL condition. In addition, the simulations of the realistic building cluster experiments showed that the density of buildings was a crucial factor determining the dynamic effects of the PBL structure on the flow patterns. The momentum field within a denser building configuration was mostly transported from the upper flow, and was more sensitive to the PBL structures than that of the sparser building configuration. Finally, it was recommended to use the Mellor-Yamada-Nakanishi-Niino（MYNN） PBL scheme, which can explicitly output the needed turbulent variables, to provide the boundary conditions to the CFD simulation.展开更多
文摘With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based onUAV is urgently needed to avoid major safety accidents.At the same time,the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of devices.As a result,the Dispersed Computing(DCOMP)architecture enables collaborative computing between devices in the Internet of Everything(IoE),promotes low-latency and efficient cross-wide applications,and meets users’growing needs for computing performance and service quality.This paper focuses on examining the resource allocation challenge within a dispersed computing environment that utilizes UAV inspection tracks.Furthermore,the system takes into account both resource constraints and computational constraints and transforms the optimization problem into an energy minimization problem with computational constraints.The Markov Decision Process(MDP)model is employed to capture the connection between the dispersed computing resource allocation strategy and the system environment.Subsequently,a method based on Double Deep Q-Network(DDQN)is introduced to derive the optimal policy.Simultaneously,an experience replay mechanism is implemented to tackle the issue of increasing dimensionality.The experimental simulations validate the efficacy of the method across various scenarios.
基金supported in part by the National Science Foundation Project of P.R.China (No.61931001)the Fundamental Research Funds for the Central Universities under Grant (No.FRFAT-19-010)the Scientific and Technological Innovation Foundation of Foshan,USTB (No.BK20AF003)。
文摘Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.
基金supported in part by the National Science Foundation Project of P.R.China(No.61931001)the Scientific and Technological Innovation Foundation of Foshan,USTB(No.BK20AF003)。
文摘Dispersed computing can link all devices with computing capabilities on a global scale to form a fully decentralized network,which can make full use of idle computing resources.Realizing the overall resource allocation of the dispersed computing system is a significant challenge.In detail,by jointly managing the task requests of external users and the resource allocation of the internal system to achieve dynamic balance,the efficient and stable operation of the system can be guaranteed.In this paper,we first propose a task-resource joint management model,which quantifies the dynamic transformation relationship between the resources consumed by task requests and the resources occupied by the system in dispersed computing.Secondly,to avoid downtime caused by an overload of resources,we introduce intelligent control into the task-resource joint management model.The existence and stability of the positive periodic solution of the model can be obtained by theoretical analysis,which means that the stable operation of dispersed computing can be guaranteed through the intelligent feedback control strategy.Additionally,to improve the system utilization,the task-resource joint management model with bi-directional intelligent control is further explored.Setting control thresholds for the two resources not only reverse restrains the system resource overload,but also carries out positive incentive control when a large number of idle resources appear.The existence and stability of the positive periodic solution of the model are proved theoretically,that is,the model effectively avoids the two extreme cases and ensure the efficient and stable operation of the system.Finally,numerical simulation verifies the correctness and validity of the theoretical results.
基金supported by the National Natural Science Foundation of China(Grant No.62072031)the Applied Basic Research Foundation of Yunnan Province(Grant No.2019FD071)the Yunnan Scientific Research Foundation Project(Grant 2019J0187).
文摘With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points(NCPs).Considering the amount of task data and the idle resources of NCPs,a computing resource scheduling model for NCPs is established.Taking the heterogeneous task execution delay threshold as a constraint,the optimization problem is described as the problem of maximizing the utilization of computing resources by NCPs.The proposed problem is proven to be NP-hard by using the method of reduction to a 0-1 knapsack problem.A many-to-many matching algorithm based on resource preferences is proposed.The algorithm first establishes the mutual preference lists based on the adaptability of the task requirements and the resources provided by NCPs.This enables the filtering out of un-schedulable NCPs in the initial stage of matching,reducing the solution space dimension.To solve the matching problem between ICVs and NCPs,a new manyto-many matching algorithm is proposed to obtain a unique and stable optimal matching result.The simulation results demonstrate that the proposed scheme can improve the resource utilization of NCPs by an average of 9.6%compared to the reference scheme,and the total performance can be improved by up to 15.9%.
基金Supported by the National Natural Science Foundation of China under Grand No 10374098.
文摘We investigate the elastic waves excited by an arbitrary plane piezoelectric source on the surface of a multilayered medium. Based on the previous studies, the 2D elastic wavefield in the multilayered medium is extended to 3D space. The propagator matrix for the 3D wavefield is investigated and the displacement-stress response for the boundary conditions is obtained. The excitation and propagation of the Rayleigh and Love waves are analysed further. It is found that the propagation velocity of the Rayleigh and Love waves does not depend on the propagation azimuth θ in the plane parallel to the free surface of the multilayered medium while the displacement is strongly dependent on the azimuth θ.
文摘In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approximate the high-order spatial differential operators and transform the seismic wave equations into semi-discrete ordinary differential equations （ODEs）. Then, the converted ODE system is solved by the exponential time difference （ETD） method. We investigate the properties of NETD in detail, including the stability condition for 1-D and 2-D cases, the theoretical and relative errors, the numerical dispersion relation for the 2-D acoustic case, and the computational efficiency. In order to further validate the method, we apply it to simulating acoustic/elastic wave propagation in mul- tilayer models which have strong contrasts and complex heterogeneous media, e.g., the SEG model and the Mar- mousi model. From our theoretical analyses and numerical results, the NETD can suppress numerical dispersion effectively by using the displacement and gradient to approximate the high-order spatial derivatives. In addition, because NETD is based on the structure of the Lie group method which preserves the quantitative properties of differential equations, it can achieve more accurate results than the classical methods.
基金supported by the China Meteorological Administration Special Public Welfare Research Fund (No. GYHY201106033)the National Natural Science Foundation of China (No. 41175004)
文摘The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computational Fluid Dynamics（CFD） model. The boundary conditions of different PBL structures/conditions were provided by simulations of the Weather Researching and Forecasting model. The simulated results of the idealized 2D and 3D street canyon experiments showed that the increment of PBL instability favored the downward transport of momentum from the upper flow above the roof to the pedestrian level within the street canyon. As a result, the flow and turbulent fields within the street canyon under the more unstable PBL condition are stronger. Therefore, more pollutants within the street canyon would be removed by the stronger advection and turbulent diffusion processes under the unstable PBL condition. On the contrary, more pollutants would be concentrated in the street canyon under the stable PBL condition. In addition, the simulations of the realistic building cluster experiments showed that the density of buildings was a crucial factor determining the dynamic effects of the PBL structure on the flow patterns. The momentum field within a denser building configuration was mostly transported from the upper flow, and was more sensitive to the PBL structures than that of the sparser building configuration. Finally, it was recommended to use the Mellor-Yamada-Nakanishi-Niino（MYNN） PBL scheme, which can explicitly output the needed turbulent variables, to provide the boundary conditions to the CFD simulation.
