Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological inn...Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.展开更多
Tethered satellite systems（TSSs） have attracted significant attention due to their potential and valuable applications for scientific research. With the development of various launched on-orbit missions, the deploym...Tethered satellite systems（TSSs） have attracted significant attention due to their potential and valuable applications for scientific research. With the development of various launched on-orbit missions, the deployment of tethers is considered a crucial technology for operation of a TSS. Both past orbiting experiments and numerical results have shown that oscillations of the deployed tether due to the Coriolis force and environmental perturbations are inevitable and that the impact between the space tether and end-body at the end of the deployment process leads to complicated nonlinear phenomena. Hence, a set of suitable control methods plays a fundamental role in tether deployment. This review article summarizes previous work on aspects of the dynamics, control, and ground-based experiments of tether deployment. The relevant basic principles, analytical expressions, simulation cases, and experimental results are presented as well.展开更多
With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally...With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.展开更多
Deployment of buoy systems is one of the most important procedures for the operation of buoy system. In the present study, a single-point mooring buoy system which contains surface buoy, cable segments with components...Deployment of buoy systems is one of the most important procedures for the operation of buoy system. In the present study, a single-point mooring buoy system which contains surface buoy, cable segments with components, anchor and so on is modeled by applying multi-body dynamics method. The motion equations are developed in discrete node description and fully Cartesian coordinates. Then numerical method is used to solve the ordinary differential equations and dynamics simulations are achieved while anchor is casting from board. The trajectories and velocities of different nodes without current and with current in buoy system are obtained. The transient tension force of each part of the cable is analyzed in the process of deployment. Numerical results indicate that the transient payload increases to a peak value when the anchor is touching the seabed and the maximum tension force will vary with different floating configuration. This work is helpful for design and deployment planning of buoy system.展开更多
The tether deployment of a tethered satellite system involves the consideration of complex dynamic properties of the tether,such as large deformation,slack,and even rebound,and therefore,the dynamic modelling of the t...The tether deployment of a tethered satellite system involves the consideration of complex dynamic properties of the tether,such as large deformation,slack,and even rebound,and therefore,the dynamic modelling of the tether is necessary for performing a dynamic analysis of the system.For a variablelength tether element,the absolute nodal coordinate formulation(ANCF)in the framework of the arbitrary Lagrange-Euler(ALE)description was used to develop a precise dynamic model of a tethered satellite.The model considered the gravitational gradient force and Coriolis force in the orbital coordinate frame,and it was validated through numerical simulation.In the presence of dynamic constraints,a deployment velocity of the tether was obtained by an optimal procedure.In the simulation,rebound behavior of the tethered satellite system was observed when the ANCF-ALE model was employed.Notably,the rebound behavior cannot be predicted by the traditional dumbbell model.Furthermore,an improved optimal deployment velocity was developed.Simulation results indicated that the rebound phenomenon was eliminated,and smooth deployment as well as a stable state of the station-keeping process were achieved.Additionally,the swing amplitude in the station-keeping phase decreased when a deployment strategy based on the improved optimal deployment velocity was used.展开更多
In this paper,a methodology for designing mooring system deployment for vessels at varying water depths is proposed.The Non-dominated Sorting Genetic Algorithm-II(NSGA-II)is combined with a self-dependently developed ...In this paper,a methodology for designing mooring system deployment for vessels at varying water depths is proposed.The Non-dominated Sorting Genetic Algorithm-II(NSGA-II)is combined with a self-dependently developed vessel-mooring coupled program to find the optimal mooring system deployment considering both station-keeping requirements and the safety of the mooring system.Two case studies are presented to demonstrate the methodology by designing the mooring system deployments for a very large floating structure(VLFS)module and a semi-submersible platform respectively at three different water depths.It can be concluded from the obtained results that the mooring system can achieve a better station-keeping ability with relatively shorter mooring line when deployed in the shallow water.The safety factor of mooring line is mainly dominated by the maximum instantaneous tension increment in the shallow water,while the pre-tension has a decisive influence on the safety factor of the mooring line in the deep water.展开更多
Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first fo...Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.展开更多
Submersible buoy systems are widely used for oceanographic research,ocean engineering and coastal defense.Severe sea environment has obvious effects on the dynamics of submersible buoy systems.Huge tension can occur a...Submersible buoy systems are widely used for oceanographic research,ocean engineering and coastal defense.Severe sea environment has obvious effects on the dynamics of submersible buoy systems.Huge tension can occur and may cause the snap of cables,especially during the deployment period.This paper studies the deployment dynamics of submersible buoy systems with numerical and experimental methods.By applying the lumped mass approach,a three-dimensional multi-body model of submersible buoy system is developed considering the hydrodynamic force,tension force and impact force between components of submersible buoy system and seabed.Numerical integration method is used to solve the differential equations.The simulation output includes tension force,trajectory,profile and dropping location and impact force of submersible buoys.In addition,the deployment experiment of a simplified submersible buoy model was carried out.The profile and different nodes' velocities of the submersible buoy are obtained.By comparing the results of the two methods,it is found that the numerical model well simulates the actual process and conditions of the experiment.The simulation results agree well with the results of the experiment such as gravity anchor's location and velocities of different nodes of the submersible buoy.The study results will help to understand the conditions of submersible buoy's deployment,operation and recovery,and can be used to guide the design and optimization of the system.展开更多
Wireless avionics intra-communications(WAIC)is an emergent research topic,since it can improve fuel efficiency and enhance aircraft safety significantly.However,there are numerous baffles in an aircraft,e.g.,seats and...Wireless avionics intra-communications(WAIC)is an emergent research topic,since it can improve fuel efficiency and enhance aircraft safety significantly.However,there are numerous baffles in an aircraft,e.g.,seats and cabin bulkheads,resulting in serious blockage and even destroying wireless communications.Thus,this paper focuses on the reconfigurable intelligent surface(RIS)deployment issue of RIS-assisted WAIC systems,to solve the blockage problem caused by baffles.We first propose the mirror-symmetric imaging principle for mathematically analyzing electromagnetic(EM)wave propagation in a metal cuboid,which is a typical structure of WAIC systems.Based on the mirror-symmetric imaging principle,the mathematical channel model in a metal cuboid is deduced in detail.In addition,we develop an objective function of RIS's location and deduce the optimal RIS deployment location based on the geometric center optimization lemma.A two-dimensional gravity center search algorithm is then presented.Simulation results show that the designed RIS deployment can greatly increase the received power and efficiently solve the blockage problem in the aircraft.展开更多
With the rapid and wide deployment of renewable energy,the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance.The output power of renewable energy is...With the rapid and wide deployment of renewable energy,the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance.The output power of renewable energy is uncertain,and thus flexible regulation for the power balance is highly demanded.Considering the multi-timescale output characteristics of renewable energy,a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper.Through the multi-timescale decomposition algorithm on the basis of mathematical morphology,the multi-timescale components are separated to determine the flexibility requirements on different timescales.Based on the obtained flexibility requirements,a multi-timescale energy resources deployment model based on bi-level optimization is established considering the economic performance and the flexibility of system operation.This optimization model can allocate corresponding flexibility resources according to the economy,flexibility and reliability requirements of the power system,and achieve the trade-off between them.Finally,case studies demonstrate the effectiveness of our model and method.展开更多
Discusses in detail the deploying strategies and feature of the motion of the Tethered Space System and the effects of some parameters, such as the property and initial length of the tether, the perturbation of the at...Discusses in detail the deploying strategies and feature of the motion of the Tethered Space System and the effects of some parameters, such as the property and initial length of the tether, the perturbation of the atmosphere, the ellipse of the orbit and the mass distribution of the system and points out the deploying strategy is based on the controlling of tension and the length of tether. And concludes from the computer simulation results of a tethered atmosphere probing satellite deployment that the deploying strategy presented does work well.展开更多
As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven ...As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven mining equipment to solve the problems of high energy consumption and insufficient power coupling of current equipment.This study proposed a design of a hybrid power system for underground Load Haul Dump(LHD).The proposed design integrated Quality Function Deployment(QFD)and Theory of Inventive Problem Solving(TRIZ).It identified 7 user requirements and 10 related technical features,formulated 11 innovative design solutions,and ultimately adopting an electric drive hybrid power scheme.This scheme effectively addressesd power transmission coupling problems and improve the efficiency of loaders.A 6 m³hybrid power loader prototype has been developed,which reduces operational energy consumption and advances the electrification and green,low-carbon evolution of mining equipment.展开更多
This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users....This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users.An optimization problem is formulated by deploying the UAV for maximizing the sum rate of the two users.In order to solve the optimization problem,the feasible solution region is first reduced to a line segment between two users.Then,the optimization problem is simplified to a univariate problem,which can be solved by derivation under a certain situation,and the corresponding analytical solution is also provided.Moreover,a generalized algorithm,which considers 2 situations,is proposed to further determine the optimal UAV’s location.Specifically,four cases are discussed in the first situation.Extensive simulations are depicted to demonstrate effectiveness of the proposed algorithm and its superiority over the benchmarks in maximizing the two users’sum rate.展开更多
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate des...Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.展开更多
The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless cove...The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and acc...The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and accurate landing,a multidimensional parachute deployment box for determining deployment condition during Mars landing was proposed.First,an extremerange optimization model was established,synthesizing the dynamics and constraints of both parachute descent and powered descent phases.Then,on the basis of the two-dimensional altitude-velocity deployment box,a multi-dimensional parachute deployment box characterized by altitude,velocity,flight-path angle,and extreme range was constructed through the integration of extreme range information.Furthermore,an evaluation index for landing precision was formulated and a deployment control logic was proposed for minimizing landing deviation.Finally,the proposed deployment box was simulated in a Mars landing mission.The results demonstrate that the proposed box effectively satisfies safe deployment and landing precision demands,eliminating the range-to-go error at the terminal of the entry phase.展开更多
基金supported by the National Natural Science Foundation of China(72072047)the Fundamental Research Funds for the Central Universities(HIT.HSS.ESD202310)+3 种基金the Research Project on Graduates’Education and Teaching Reform of HIT(23MS011)the research Project on Higher Education of Heilongjiang Higher Education Association(23GJYBC011)the Natural Science Foundation of Shandong Province(ZR2023QG010)the Shandong Philosophy and Social Science Research Project(22CSDJ03).
文摘Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
基金funded by the National Natural Science Foundation of China (11672125, 11732006)the Civil Aerospace Pre-research Project of China (D010305)+1 种基金the Research Fund of State Key Laboratory of Mechanics and Control of Mechanical Structures (Nanjing University of Aeronautics and Astronautics, MCMS-0116K01)the Fundamental Research Funds for the Central Universities (NS2016009)
文摘Tethered satellite systems（TSSs） have attracted significant attention due to their potential and valuable applications for scientific research. With the development of various launched on-orbit missions, the deployment of tethers is considered a crucial technology for operation of a TSS. Both past orbiting experiments and numerical results have shown that oscillations of the deployed tether due to the Coriolis force and environmental perturbations are inevitable and that the impact between the space tether and end-body at the end of the deployment process leads to complicated nonlinear phenomena. Hence, a set of suitable control methods plays a fundamental role in tether deployment. This review article summarizes previous work on aspects of the dynamics, control, and ground-based experiments of tether deployment. The relevant basic principles, analytical expressions, simulation cases, and experimental results are presented as well.
基金supported by the National Outstanding Youth Science Foundation (60925011)the National Natural Science Foundation of China (61203181)
文摘With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
基金supported by the National Natural Science Foundation of China (Grant No. 51175484)the Science Foundation of Shandong Province (Grant No. ZR2010EM052)
文摘Deployment of buoy systems is one of the most important procedures for the operation of buoy system. In the present study, a single-point mooring buoy system which contains surface buoy, cable segments with components, anchor and so on is modeled by applying multi-body dynamics method. The motion equations are developed in discrete node description and fully Cartesian coordinates. Then numerical method is used to solve the ordinary differential equations and dynamics simulations are achieved while anchor is casting from board. The trajectories and velocities of different nodes without current and with current in buoy system are obtained. The transient tension force of each part of the cable is analyzed in the process of deployment. Numerical results indicate that the transient payload increases to a peak value when the anchor is touching the seabed and the maximum tension force will vary with different floating configuration. This work is helpful for design and deployment planning of buoy system.
基金supported by the Natural Science Foundation of Shaanxi Province,China(2020JQ-288)Science and Technology on Space Intelligent Control Laboratory,China(HTKJ2019KL502016)+1 种基金China Scholarship Council(201806120093)National Natural Science Foundation of China(61903289).
文摘The tether deployment of a tethered satellite system involves the consideration of complex dynamic properties of the tether,such as large deformation,slack,and even rebound,and therefore,the dynamic modelling of the tether is necessary for performing a dynamic analysis of the system.For a variablelength tether element,the absolute nodal coordinate formulation(ANCF)in the framework of the arbitrary Lagrange-Euler(ALE)description was used to develop a precise dynamic model of a tethered satellite.The model considered the gravitational gradient force and Coriolis force in the orbital coordinate frame,and it was validated through numerical simulation.In the presence of dynamic constraints,a deployment velocity of the tether was obtained by an optimal procedure.In the simulation,rebound behavior of the tethered satellite system was observed when the ANCF-ALE model was employed.Notably,the rebound behavior cannot be predicted by the traditional dumbbell model.Furthermore,an improved optimal deployment velocity was developed.Simulation results indicated that the rebound phenomenon was eliminated,and smooth deployment as well as a stable state of the station-keeping process were achieved.Additionally,the swing amplitude in the station-keeping phase decreased when a deployment strategy based on the improved optimal deployment velocity was used.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51709170 and 51979167)the Ministry of Industry and Information Technology of China(Mooring position technology:floating support platform engineering(II))the Shanghai Sailing Program(Grant No.17YF1409700)
文摘In this paper,a methodology for designing mooring system deployment for vessels at varying water depths is proposed.The Non-dominated Sorting Genetic Algorithm-II(NSGA-II)is combined with a self-dependently developed vessel-mooring coupled program to find the optimal mooring system deployment considering both station-keeping requirements and the safety of the mooring system.Two case studies are presented to demonstrate the methodology by designing the mooring system deployments for a very large floating structure(VLFS)module and a semi-submersible platform respectively at three different water depths.It can be concluded from the obtained results that the mooring system can achieve a better station-keeping ability with relatively shorter mooring line when deployed in the shallow water.The safety factor of mooring line is mainly dominated by the maximum instantaneous tension increment in the shallow water,while the pre-tension has a decisive influence on the safety factor of the mooring line in the deep water.
基金supported by the National Natural Science Foundation of China(71171197)the National Basic Research Program of China(973 Program)(613154)
文摘Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.
基金supported by the Program for Excellent University Talents in New Century (NCET-12-0500)the National Natural Science Foundation of China (No.51175484)+2 种基金the Science Foundation of Shandong Province (No.ZR2010EM052)the support of the Project 111 (No.B14028)the Key Ocean Engineering Laboratory of Shandong Province
文摘Submersible buoy systems are widely used for oceanographic research,ocean engineering and coastal defense.Severe sea environment has obvious effects on the dynamics of submersible buoy systems.Huge tension can occur and may cause the snap of cables,especially during the deployment period.This paper studies the deployment dynamics of submersible buoy systems with numerical and experimental methods.By applying the lumped mass approach,a three-dimensional multi-body model of submersible buoy system is developed considering the hydrodynamic force,tension force and impact force between components of submersible buoy system and seabed.Numerical integration method is used to solve the differential equations.The simulation output includes tension force,trajectory,profile and dropping location and impact force of submersible buoys.In addition,the deployment experiment of a simplified submersible buoy model was carried out.The profile and different nodes' velocities of the submersible buoy are obtained.By comparing the results of the two methods,it is found that the numerical model well simulates the actual process and conditions of the experiment.The simulation results agree well with the results of the experiment such as gravity anchor's location and velocities of different nodes of the submersible buoy.The study results will help to understand the conditions of submersible buoy's deployment,operation and recovery,and can be used to guide the design and optimization of the system.
基金supported by the National Natural Science Foundation of China under Grand No.62071148 and No.62171151partly by the Natural Science Foundation of Heilongjiang Province of China under Grand No.YQ2019F009partly by the Fundamental Research Funds for Central Universities under Grand No.HIT.OCEF.2021012。
文摘Wireless avionics intra-communications(WAIC)is an emergent research topic,since it can improve fuel efficiency and enhance aircraft safety significantly.However,there are numerous baffles in an aircraft,e.g.,seats and cabin bulkheads,resulting in serious blockage and even destroying wireless communications.Thus,this paper focuses on the reconfigurable intelligent surface(RIS)deployment issue of RIS-assisted WAIC systems,to solve the blockage problem caused by baffles.We first propose the mirror-symmetric imaging principle for mathematically analyzing electromagnetic(EM)wave propagation in a metal cuboid,which is a typical structure of WAIC systems.Based on the mirror-symmetric imaging principle,the mathematical channel model in a metal cuboid is deduced in detail.In addition,we develop an objective function of RIS's location and deduce the optimal RIS deployment location based on the geometric center optimization lemma.A two-dimensional gravity center search algorithm is then presented.Simulation results show that the designed RIS deployment can greatly increase the received power and efficiently solve the blockage problem in the aircraft.
基金supported by the NationalNatural Science Foundation of China(Grant No.52107129).
文摘With the rapid and wide deployment of renewable energy,the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance.The output power of renewable energy is uncertain,and thus flexible regulation for the power balance is highly demanded.Considering the multi-timescale output characteristics of renewable energy,a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper.Through the multi-timescale decomposition algorithm on the basis of mathematical morphology,the multi-timescale components are separated to determine the flexibility requirements on different timescales.Based on the obtained flexibility requirements,a multi-timescale energy resources deployment model based on bi-level optimization is established considering the economic performance and the flexibility of system operation.This optimization model can allocate corresponding flexibility resources according to the economy,flexibility and reliability requirements of the power system,and achieve the trade-off between them.Finally,case studies demonstrate the effectiveness of our model and method.
文摘Discusses in detail the deploying strategies and feature of the motion of the Tethered Space System and the effects of some parameters, such as the property and initial length of the tether, the perturbation of the atmosphere, the ellipse of the orbit and the mass distribution of the system and points out the deploying strategy is based on the controlling of tension and the length of tether. And concludes from the computer simulation results of a tethered atmosphere probing satellite deployment that the deploying strategy presented does work well.
文摘As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven mining equipment to solve the problems of high energy consumption and insufficient power coupling of current equipment.This study proposed a design of a hybrid power system for underground Load Haul Dump(LHD).The proposed design integrated Quality Function Deployment(QFD)and Theory of Inventive Problem Solving(TRIZ).It identified 7 user requirements and 10 related technical features,formulated 11 innovative design solutions,and ultimately adopting an electric drive hybrid power scheme.This scheme effectively addressesd power transmission coupling problems and improve the efficiency of loaders.A 6 m³hybrid power loader prototype has been developed,which reduces operational energy consumption and advances the electrification and green,low-carbon evolution of mining equipment.
基金the National Natural Science Foundation of China(No.61702258,61901211)the Natural Science Foundation of Jiangsu Province(No.BK20170766).
文摘This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users.An optimization problem is formulated by deploying the UAV for maximizing the sum rate of the two users.In order to solve the optimization problem,the feasible solution region is first reduced to a line segment between two users.Then,the optimization problem is simplified to a univariate problem,which can be solved by derivation under a certain situation,and the corresponding analytical solution is also provided.Moreover,a generalized algorithm,which considers 2 situations,is proposed to further determine the optimal UAV’s location.Specifically,four cases are discussed in the first situation.Extensive simulations are depicted to demonstrate effectiveness of the proposed algorithm and its superiority over the benchmarks in maximizing the two users’sum rate.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金This work was supported in part by the Natural Science Foundation of the Education Department of Henan Province(Grant 22A520025)the National Natural Science Foundation of China(Grant 61975053)the National Key Research and Development of Quality Information Control Technology for Multi-Modal Grain Transportation Efficient Connection(2022YFD2100202).
文摘Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.
文摘The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
基金Supported by the National Natural Science Foundation of China(62073034)。
文摘The parachute deployment conditions during the terminal entry phase in Mars landing missions exhibit critical impact on landing precision.In this article,aiming at the requirements of safe parachute deployment and accurate landing,a multidimensional parachute deployment box for determining deployment condition during Mars landing was proposed.First,an extremerange optimization model was established,synthesizing the dynamics and constraints of both parachute descent and powered descent phases.Then,on the basis of the two-dimensional altitude-velocity deployment box,a multi-dimensional parachute deployment box characterized by altitude,velocity,flight-path angle,and extreme range was constructed through the integration of extreme range information.Furthermore,an evaluation index for landing precision was formulated and a deployment control logic was proposed for minimizing landing deviation.Finally,the proposed deployment box was simulated in a Mars landing mission.The results demonstrate that the proposed box effectively satisfies safe deployment and landing precision demands,eliminating the range-to-go error at the terminal of the entry phase.
