Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements,the computing force network(CFN)has become a hot research subject.The primary...Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements,the computing force network(CFN)has become a hot research subject.The primary CFN challenge is to leverage network resources and computing resources.Although recent advances in deep reinforcement learning(DRL)have brought significant improvement in network optimization,these methods still suffer from topology changes and fail to generalize for those topologies not seen in training.This paper proposes a graph neural network(GNN)based DRL framework to accommodate network trafic and computing resources jointly and efficiently.By taking advantage of the generalization capability in GNN,the proposed method can operate over variable topologies and obtain higher performance than the other DRL methods.展开更多
Under the development of computing and network convergence,considering the computing and network resources of multiple providers as a whole in a computing force network(CFN)has gradually become a new trend.However,sin...Under the development of computing and network convergence,considering the computing and network resources of multiple providers as a whole in a computing force network(CFN)has gradually become a new trend.However,since each computing and network resource provider(CNRP)considers only its own interest and competes with other CNRPs,introducing multiple CNRPs will result in a lack of trust and difficulty in unified scheduling.In addition,concurrent users have different requirements,so there is an urgent need to study how to optimally match users and CNRPs on a many-to-many basis,to improve user satisfaction and ensure the utilization of limited resources.In this paper,we adopt a reputation model based on the beta distribution function to measure the credibility of CNRPs and propose a performance-based reputation update model.Then,we formalize the problem into a constrained multi-objective optimization problem and find feasible solutions using a modified fast and elitist non-dominated sorting genetic algorithm(NSGA-II).We conduct extensive simulations to evaluate the proposed algorithm.Simulation results demonstrate that the proposed model and the problem formulation are valid,and the NSGA-II is effective and can find the Pareto set of CFN,which increases user satisfaction and resource utilization.Moreover,a set of solutions provided by the Pareto set give us more choices of the many-to-many matching of users and CNRPs according to the actual situation.展开更多
We detect strong force networks in a dense high-shear system and study their structure and stability in response to variations in the shearing rate. The presence of strong force networks, which usually have a heteroge...We detect strong force networks in a dense high-shear system and study their structure and stability in response to variations in the shearing rate. The presence of strong force networks, which usually have a heterogeneous structure, restricts particle movements and can impose non-local mechanisms of momentum transfer. We identify such networks in a dense high-shear system using a community detec- tion algorithm. Moreover, we explain the association between the mechanisms of momentum transfer and the structure, population, strength, and stability of the force networks by tracking the spatial and temporal evolution of the detected networks. In addition, we show that the assumption of a monodis- perse assembly of particles leads to an unrealistic enlargement of the force networks, underestimating both the rate of energy dissipation and the rate of mixing.展开更多
Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm reli...Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm relies on users select cost or time priority,then scheduling to meet the requirements of users.However,this priority strategy of users is relatively simple,and cannot adapt to dynamic change of resources,it is inevitable to reduce the QoS.In order to improve QoS,we refer to the economic model and resource scheduling model of cloud computing,use SAL(Service Level Agreement) as pricing strategy,on the basis of DBC algorithm,propose an DABP(Deadline And Budget Priority based on DBC) algorithm for ForCES networks,DABP combines both budget and time priority to scheduling.In simulation and test,we compare the task finish time and cost of DABP algorithm with DP(Deadline Priority) algorithm and BP(Budget Priority) algorithm,the analysis results show that DABP algorithm make the task complete with less cost within deadline,benifical to load balancing of ForCES networks.展开更多
By minimizing the enthalpy of packings of frictionless particles, we obtain jammed solids at desired pressures and hence investigate the jamming transition with and without shear. Typical scaling relations of the jamm...By minimizing the enthalpy of packings of frictionless particles, we obtain jammed solids at desired pressures and hence investigate the jamming transition with and without shear. Typical scaling relations of the jamming transition are recovered in both cases. In contrast to systems without shear, shear-driven jamming transition occurs at a higher packing fraction and the jammed solids are more rigid with an anisotropic force network. Furthermore, by introducing the macrofriction coefficient, we propose an explanation of the packing fraction gap between sheared and non-sheared systems at fixed pressure.展开更多
By minimizing a thermodynamic-like potential, we unbiasedly sample the potential energy landscape of soft and frictionless spheres under a constant shear stress. We obtain zero-temperature jammed states under desired ...By minimizing a thermodynamic-like potential, we unbiasedly sample the potential energy landscape of soft and frictionless spheres under a constant shear stress. We obtain zero-temperature jammed states under desired shear stresses and investigate their mechanical properties as a function of the shear stress. As a comparison, we also obtain the jammed states from the quasistatic-shear sampling in which the shear stress is not well-controlled. Although the yield stresses determined by both samplings show the same power-law scaling with the compression from the jamming transition point J at zero temperature and shear stress, for finite size systems the quasistatic-shear sampling leads to a lower yield stress and a higher critical volume fraction at point J. The shear modulus of the jammed solids decreases with increasing shear stress. However, the shear modulus does not decay to zero at yielding. This discontinuous change of the shear modulus implies the discontinuous nature of the unjamming transition under nonzero shear stress, which is further verified by the observation of a discontinuous jump in the pressure from the jammed solids to the shear flows. The pressure jump decreases upon decompression and approaches zero at the critical-like point J, in analogy with the well-known phase transitions under an external field. The analysis of the force networks in the jammed solids reveals that the force distribution is more sensitive to the increase of the shear stress near point J. The force network anisotropy increases with increasing shear stress. The weak particle contacts near the average force and under large shear stresses it exhibit an asymmetric angle distribution.展开更多
The crowd evacuation of pairs of pedestrians(i.e.pairs consisting of a parent and a child)is numerically investigated.Here,it is assumed that all pedestrians have their own partners,and move randomly inside the bounde...The crowd evacuation of pairs of pedestrians(i.e.pairs consisting of a parent and a child)is numerically investigated.Here,it is assumed that all pedestrians have their own partners,and move randomly inside the bounded domain of the right-hand room as an initial state.All pedestrians start their evacuations after they contact their partners.The evacuations are completed by the transfer of all the pairs from the right-hand room to the left-hand room through an exit.A frozen swarm tends to appear in the right-hand room as the total number of pedestrians increases.The frozen swarm moves without changing its form,unless it is dissolved by a strong collision with a pair of pedestrians that comes back from the left-hand room by accident.Finally,the evacuation speed also depends on the area of the Escape Zone,whereas an obstacle placed in front of an exit also changes the speed of the evacuation in accordance with the type of motion of the children.展开更多
We present a visual analysis environment based on a multi-scale partitioning of a 2d domain intoregions bounded by cycles in weighted planar embedded graphs.The work has been inspired by anapplication in granular mate...We present a visual analysis environment based on a multi-scale partitioning of a 2d domain intoregions bounded by cycles in weighted planar embedded graphs.The work has been inspired by anapplication in granular materials research,where the question of scale plays a fundamental role inthe analysis of material properties.We propose an efficient algorithm to extract the hierarchical cyclestructure using persistent homology.The core of the algorithm is a filtration on a dual graph exploitingAlexander’s duality.The resulting partitioning is the basis for the derivation of statistical properties thatcan be explored in a visual environment.We demonstrate the proposed pipeline on a few syntheticand one real-world dataset.展开更多
基金supported by the Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements,the computing force network(CFN)has become a hot research subject.The primary CFN challenge is to leverage network resources and computing resources.Although recent advances in deep reinforcement learning(DRL)have brought significant improvement in network optimization,these methods still suffer from topology changes and fail to generalize for those topologies not seen in training.This paper proposes a graph neural network(GNN)based DRL framework to accommodate network trafic and computing resources jointly and efficiently.By taking advantage of the generalization capability in GNN,the proposed method can operate over variable topologies and obtain higher performance than the other DRL methods.
基金supported by the National Natural Science Foundation of China(No.2022ZD0115303)the 2023 Beijing Outstanding Young Engineers Innovation Studio,Chinathe Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Foundation(No.CMYJY-202200536)。
文摘Under the development of computing and network convergence,considering the computing and network resources of multiple providers as a whole in a computing force network(CFN)has gradually become a new trend.However,since each computing and network resource provider(CNRP)considers only its own interest and competes with other CNRPs,introducing multiple CNRPs will result in a lack of trust and difficulty in unified scheduling.In addition,concurrent users have different requirements,so there is an urgent need to study how to optimally match users and CNRPs on a many-to-many basis,to improve user satisfaction and ensure the utilization of limited resources.In this paper,we adopt a reputation model based on the beta distribution function to measure the credibility of CNRPs and propose a performance-based reputation update model.Then,we formalize the problem into a constrained multi-objective optimization problem and find feasible solutions using a modified fast and elitist non-dominated sorting genetic algorithm(NSGA-II).We conduct extensive simulations to evaluate the proposed algorithm.Simulation results demonstrate that the proposed model and the problem formulation are valid,and the NSGA-II is effective and can find the Pareto set of CFN,which increases user satisfaction and resource utilization.Moreover,a set of solutions provided by the Pareto set give us more choices of the many-to-many matching of users and CNRPs according to the actual situation.
文摘We detect strong force networks in a dense high-shear system and study their structure and stability in response to variations in the shearing rate. The presence of strong force networks, which usually have a heterogeneous structure, restricts particle movements and can impose non-local mechanisms of momentum transfer. We identify such networks in a dense high-shear system using a community detec- tion algorithm. Moreover, we explain the association between the mechanisms of momentum transfer and the structure, population, strength, and stability of the force networks by tracking the spatial and temporal evolution of the detected networks. In addition, we show that the assumption of a monodis- perse assembly of particles leads to an unrealistic enlargement of the force networks, underestimating both the rate of energy dissipation and the rate of mixing.
基金This work was supported in part by a grant from the National Basic Research Program of China(973 Program) under Grant No.2012CB315902,the National Natural Science Foundation of China under Grant No.61379120,61170215,the Program for Zhejiang Leading Team of Science and Technology Innovation under Grant No.2011R50010-12,2011R50010-18.Zhejiang Provincial Key Laboratory of New Network Standards and Technologies (NNST)
文摘Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm relies on users select cost or time priority,then scheduling to meet the requirements of users.However,this priority strategy of users is relatively simple,and cannot adapt to dynamic change of resources,it is inevitable to reduce the QoS.In order to improve QoS,we refer to the economic model and resource scheduling model of cloud computing,use SAL(Service Level Agreement) as pricing strategy,on the basis of DBC algorithm,propose an DABP(Deadline And Budget Priority based on DBC) algorithm for ForCES networks,DABP combines both budget and time priority to scheduling.In simulation and test,we compare the task finish time and cost of DABP algorithm with DP(Deadline Priority) algorithm and BP(Budget Priority) algorithm,the analysis results show that DABP algorithm make the task complete with less cost within deadline,benifical to load balancing of ForCES networks.
基金supported by the National Natural Science Foundation of China(Grant Nos.11702289,11734014,and 11574278)the Anhui Provincial Natural Science Foundation(Grant No.1708085QA07)
文摘By minimizing the enthalpy of packings of frictionless particles, we obtain jammed solids at desired pressures and hence investigate the jamming transition with and without shear. Typical scaling relations of the jamming transition are recovered in both cases. In contrast to systems without shear, shear-driven jamming transition occurs at a higher packing fraction and the jammed solids are more rigid with an anisotropic force network. Furthermore, by introducing the macrofriction coefficient, we propose an explanation of the packing fraction gap between sheared and non-sheared systems at fixed pressure.
基金supported by the National Natural Science Foundation of China(Grant No.21325418)the National Basic Research Program of China(GrantNo.2012CB821500)+1 种基金the Chinese Academy of Sciences 100-Talent Program(Grant No.2030020004)the Fundamental Research Funds for the Central Universities,China(Grant No.2340000034)
文摘By minimizing a thermodynamic-like potential, we unbiasedly sample the potential energy landscape of soft and frictionless spheres under a constant shear stress. We obtain zero-temperature jammed states under desired shear stresses and investigate their mechanical properties as a function of the shear stress. As a comparison, we also obtain the jammed states from the quasistatic-shear sampling in which the shear stress is not well-controlled. Although the yield stresses determined by both samplings show the same power-law scaling with the compression from the jamming transition point J at zero temperature and shear stress, for finite size systems the quasistatic-shear sampling leads to a lower yield stress and a higher critical volume fraction at point J. The shear modulus of the jammed solids decreases with increasing shear stress. However, the shear modulus does not decay to zero at yielding. This discontinuous change of the shear modulus implies the discontinuous nature of the unjamming transition under nonzero shear stress, which is further verified by the observation of a discontinuous jump in the pressure from the jammed solids to the shear flows. The pressure jump decreases upon decompression and approaches zero at the critical-like point J, in analogy with the well-known phase transitions under an external field. The analysis of the force networks in the jammed solids reveals that the force distribution is more sensitive to the increase of the shear stress near point J. The force network anisotropy increases with increasing shear stress. The weak particle contacts near the average force and under large shear stresses it exhibit an asymmetric angle distribution.
文摘The crowd evacuation of pairs of pedestrians(i.e.pairs consisting of a parent and a child)is numerically investigated.Here,it is assumed that all pedestrians have their own partners,and move randomly inside the bounded domain of the right-hand room as an initial state.All pedestrians start their evacuations after they contact their partners.The evacuations are completed by the transfer of all the pairs from the right-hand room to the left-hand room through an exit.A frozen swarm tends to appear in the right-hand room as the total number of pedestrians increases.The frozen swarm moves without changing its form,unless it is dissolved by a strong collision with a pair of pedestrians that comes back from the left-hand room by accident.Finally,the evacuation speed also depends on the area of the Escape Zone,whereas an obstacle placed in front of an exit also changes the speed of the evacuation in accordance with the type of motion of the children.
基金the Wallenberg AI,Autonomous Systems and Software Program(WASP)funded by the Knut and Alice Wallenberg Foundation,the SeRC(Swedish e-Science Research Center)and the ELLIIT environment for strategic research in Sweden,the Swedish Research Council(VR)grant 2019–05487an Indo-Swedish joint network project:DST/INT/SWD/VR/P-02/2019 VR grant 2018–07085.
文摘We present a visual analysis environment based on a multi-scale partitioning of a 2d domain intoregions bounded by cycles in weighted planar embedded graphs.The work has been inspired by anapplication in granular materials research,where the question of scale plays a fundamental role inthe analysis of material properties.We propose an efficient algorithm to extract the hierarchical cyclestructure using persistent homology.The core of the algorithm is a filtration on a dual graph exploitingAlexander’s duality.The resulting partitioning is the basis for the derivation of statistical properties thatcan be explored in a visual environment.We demonstrate the proposed pipeline on a few syntheticand one real-world dataset.
