Recently, integrating Softwaredefined networking(SDN) and network functions virtualization(NFV) are proposed to address the issue that difficulty and cost of hardwarebased and proprietary middleboxes management. Howev...Recently, integrating Softwaredefined networking(SDN) and network functions virtualization(NFV) are proposed to address the issue that difficulty and cost of hardwarebased and proprietary middleboxes management. However, it lacks of a framework that orchestrates network functions to service chain in the network cooperatively. In this paper, we propose a function combination framework that can dynamically adapt the network based on the integration NFV and SDN. There are two main contributions in this paper. First, the function combination framework based on the integration of SDN and NFV is proposed to address the function combination issue, including the architecture of Service Deliver Network, the port types representing traffic directions and the explanation of terms. Second, we formulate the issue of load balance of function combination as the model minimizing the standard deviations of all servers' loads and satisfying the demand of performance and limit of resource. The least busy placement algorithm is introduced to approach optimal solution of the problem. Finally, experimental results demonstrate that the proposed method can combine functions in an efficient and scalable way and ensure the load balance of the network.展开更多
In this article we summarize some aperiodic checkpoint placement algorithms for a software system over infinite and finite operation time horizons, and compare them in terms of computational accuracy. The underlying p...In this article we summarize some aperiodic checkpoint placement algorithms for a software system over infinite and finite operation time horizons, and compare them in terms of computational accuracy. The underlying problem is formulated as the maximization of steady-state system availability and is to determine the optimal aperiodic checkpoint sequence. We present two exact computation algorithms in both forward and backward manners and two approximate ones;constant hazard approximation and fluid approximation, toward this end. In numerical examples with Weibull system failure time distribution, it is shown that the combined algorithm with the fluid approximation can calculate effectively the exact solutions on the optimal aperiodic checkpoint sequence.展开更多
To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of te...To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.展开更多
In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated....In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated. One of the key issues in designing is the system volume, which is determined by maximum interconnection distance(MID) between PEs. A novel 2 D genetic algorithm was presented in this paper at the first time, and used to solve the placement of twin butterfly multistage networks based on transmissive physical model. The experiment result shows that this algorithm case works better than other algorithm cases.展开更多
With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data proc...With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.展开更多
The Artificial Bee Colony (ABC) is one of the numerous stochastic algorithms for optimization that has been written for solving constrained and unconstrained optimization problems. This novel optimization algorithm is...The Artificial Bee Colony (ABC) is one of the numerous stochastic algorithms for optimization that has been written for solving constrained and unconstrained optimization problems. This novel optimization algorithm is very efficient and as promising as it is;it can be favourably compared to other optimization algorithms and in some cases, it has been proven to be better than some known algorithms (like Particle Swarm Optimization (PSO)), especially when used in Well placement optimization problems that can be encountered in the Petroleum industry. In this paper, the ABC algorithm has been modified to improve its speed and convergence in finding the optimum solution to a well placement optimization problem. The effects of variations of the control parameters for both algorithms were studied, as well as the algorithms’ performances in the cases studied. The modified ABC (MABC) algorithm gave better results than the Artificial Bee Colony algorithm. It was noticed that the performance of the ABC algorithm increased with increase in the number of its optimization agents for both algorithms studied. The modified ABC algorithm overcame the challenge posed by the use of uniformly generated random numbers with very rough NPV surface. This new modified ABC algorithm proposed in this work will be a great tool in optimization for the Petroleum industry as it involves Well placements for optimum oil production.展开更多
This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using c...This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.展开更多
We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first （LFF） principle,we simulate a manual packing process in which the concept of placement by stages is in...We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first （LFF） principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is （N1 ＋ N2 ） × O（ n^2 ） ＋ N3× O（n^4lgn） ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 ＋ N2 ＋ N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O（n^5lgn）. Experimental results indicate that this approach is quite promising.展开更多
Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the r...Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the related research on CPP in SDWN hasn’t modeled the energy consumption of controllers so far.To prolong the lifetime of SDWN and improve the practicability of research,we rebuilt a CPP model considering the minimal transmitted power of controllers.An adaptive controller placement algorithm(ACPA)is proposed with the following two stages.First,data field method is adopted to determine sub-networks for different network topologies.Second,for each sub-network we adopt an exhaustive method to find the optimal location which meets the minimal average transmitted power to place controller.Compared with the other algorithms,the effectiveness and efficiency of the proposed scheme are validated through simulation.展开更多
Shunt capacitors are broadly applied in distribution systems to scale down power losses, improve voltage profile and boost system capacity. The amount of capacitors added and location of deployment in the system highl...Shunt capacitors are broadly applied in distribution systems to scale down power losses, improve voltage profile and boost system capacity. The amount of capacitors added and location of deployment in the system highly determine the advantage of compensation. A novel global harmony search(GHS) algorithm in parallel with the backward/ forward sweep power flow technique and radial harmonic power flow was used to investigate the optimal placement and sizing of capacitors in radial distribution networks for minimizing power loss and total cost by taking account load unbalancing, mutual coupling and harmonics. The optimal capacitor placement outcomes show that the GHS algorithm can reduce total power losses up to 60 k W and leads to more than 18% of cost saving. The results also demonstrate that the GHS algorithm is more effective in minimization of power loss and total costs compared with genetic algorithm(GA), particle swarm optimization(PSO) and harmony search(HS) algorithm. Moreover, the proposed algorithm converges within 800 iterations and is faster in terms of computational time and gives better performance in finding optimal capacitor location and size compared with other optimization techniques.展开更多
To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched...To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.展开更多
The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap co...The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.展开更多
We present a novel paradigm of sensor placement concerning data precision and estimation.Multiple abstract sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network.These s...We present a novel paradigm of sensor placement concerning data precision and estimation.Multiple abstract sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network.These sensors can cooperate with each other to obtain a precise estimate of the quantity in a real-time manner.We consider a problem on planning a minimum-cost scheme of sensor placement with desired data precision and resource consumption.Measured data is modeled as a Gaussian random variable with a changeable variance.A gird model is used to approximate the problem.We solve the problem with a heuristic algorithm using branch-and-bound method and tabu search.Our experiments demonstrate that the algorithm is correct in a certain tolerance,and it is also efficient and scalable.展开更多
Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to cont...Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to control action and a real coded genetic algorithm then proposed to produce a global optimum solution, and proves the feasibility and advantages of this algorithm with the example of a standard test function and a two collocated actuators/sensors cantilever, and comparing the results with those given in the literatures.展开更多
In this paper a new method has been proposed to determine optimal location and best setting of Thyristor Controlled Series Compensator (TCSC). Seeking the best place is performed using the sensitivity analysis and opt...In this paper a new method has been proposed to determine optimal location and best setting of Thyristor Controlled Series Compensator (TCSC). Seeking the best place is performed using the sensitivity analysis and optimum setting of TCSC is managed using the genetic algorithm. The configuration of a typical TCSC from a steady-state perspective is the fixed capacitor with a thyristor controlled reactor (TCR). The effect of TCSC on the network can be modeled as a controllable reactance inserted in the related transmission line. This paper employs the DIgSILENT simulator and the DPL as a programming tool of the DIgSILENT to show the validity of the proposed method. The effectiveness of sug-gested approach has been tested on IEEE 14-bus system.展开更多
In this paper, we analyse the deployment of middlebox. For a given network information and policy requirements, an attempt is made to determine the optimal location of middlebox to achieve the best performance. In ter...In this paper, we analyse the deployment of middlebox. For a given network information and policy requirements, an attempt is made to determine the optimal location of middlebox to achieve the best performance. In terms of the end-to-end delay as a performance optimization index, a distributed middlebox placement algorithm based on potential game is proposed. Through extensive simulations, it demonstrates that the proposed algorithm achieves the near-optimal solution, and the end-to-end delay decreases significantly.展开更多
Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generat...Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.展开更多
Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of...Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.展开更多
基金supported by the Foundation for Innovative Research Groups of the National Science Foundation of China (Grant No.61521003)The National Basic Research Program of China(973)(Grant No.2012CB315901,2013CB329104)+1 种基金The National Natural Science Foundation of China(Grant No.61372121,61309019,61309020)The National High Technology Research and Development Program of China(863)(Grant No.2015AA016102,2013AA013505)
文摘Recently, integrating Softwaredefined networking(SDN) and network functions virtualization(NFV) are proposed to address the issue that difficulty and cost of hardwarebased and proprietary middleboxes management. However, it lacks of a framework that orchestrates network functions to service chain in the network cooperatively. In this paper, we propose a function combination framework that can dynamically adapt the network based on the integration NFV and SDN. There are two main contributions in this paper. First, the function combination framework based on the integration of SDN and NFV is proposed to address the function combination issue, including the architecture of Service Deliver Network, the port types representing traffic directions and the explanation of terms. Second, we formulate the issue of load balance of function combination as the model minimizing the standard deviations of all servers' loads and satisfying the demand of performance and limit of resource. The least busy placement algorithm is introduced to approach optimal solution of the problem. Finally, experimental results demonstrate that the proposed method can combine functions in an efficient and scalable way and ensure the load balance of the network.
文摘In this article we summarize some aperiodic checkpoint placement algorithms for a software system over infinite and finite operation time horizons, and compare them in terms of computational accuracy. The underlying problem is formulated as the maximization of steady-state system availability and is to determine the optimal aperiodic checkpoint sequence. We present two exact computation algorithms in both forward and backward manners and two approximate ones;constant hazard approximation and fluid approximation, toward this end. In numerical examples with Weibull system failure time distribution, it is shown that the combined algorithm with the fluid approximation can calculate effectively the exact solutions on the optimal aperiodic checkpoint sequence.
基金supported by the State Grid Science and Technology Project “Research on Technology System and Applications Scenarios of Artificial Intelligence in Power System” (No. SGZJ0000KXJS1800435)Key Technology Project of State Grid Shanghai Municipal Electric Power Company “Research and demonstration of Shanghai power grid reliability analysis platform”Key Technology Project of China Electric Power Research Institute “Research on setting calculation technology of power grid phase protection based on Artificial Intelligence” (JB83-19-007)
文摘To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.
基金Defense Science and Technology Pre- re-search Foundation Project!under Con-tract98J2 .5.8.JW0 30 1
文摘In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated. One of the key issues in designing is the system volume, which is determined by maximum interconnection distance(MID) between PEs. A novel 2 D genetic algorithm was presented in this paper at the first time, and used to solve the placement of twin butterfly multistage networks based on transmissive physical model. The experiment result shows that this algorithm case works better than other algorithm cases.
文摘With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.
文摘The Artificial Bee Colony (ABC) is one of the numerous stochastic algorithms for optimization that has been written for solving constrained and unconstrained optimization problems. This novel optimization algorithm is very efficient and as promising as it is;it can be favourably compared to other optimization algorithms and in some cases, it has been proven to be better than some known algorithms (like Particle Swarm Optimization (PSO)), especially when used in Well placement optimization problems that can be encountered in the Petroleum industry. In this paper, the ABC algorithm has been modified to improve its speed and convergence in finding the optimum solution to a well placement optimization problem. The effects of variations of the control parameters for both algorithms were studied, as well as the algorithms’ performances in the cases studied. The modified ABC (MABC) algorithm gave better results than the Artificial Bee Colony algorithm. It was noticed that the performance of the ABC algorithm increased with increase in the number of its optimization agents for both algorithms studied. The modified ABC algorithm overcame the challenge posed by the use of uniformly generated random numbers with very rough NPV surface. This new modified ABC algorithm proposed in this work will be a great tool in optimization for the Petroleum industry as it involves Well placements for optimum oil production.
文摘This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.
文摘We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first （LFF） principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is （N1 ＋ N2 ） × O（ n^2 ） ＋ N3× O（n^4lgn） ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 ＋ N2 ＋ N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O（n^5lgn）. Experimental results indicate that this approach is quite promising.
基金supported by the Open Research Fund of Key Laboratory of Space Utilization,Chinese Academy of Sciences(No.LSU-KFJJ-2018-06)the International Research Cooperation Seed Fund of Beijing University of Technology(No.2018B41)
文摘Controller placement problem(CPP)is a critical issue in software defined wireless networks(SDWN).Due to the limited power of wireless devices,CPP is facing the challenge of energy efficiency in SDWN.Nevertheless,the related research on CPP in SDWN hasn’t modeled the energy consumption of controllers so far.To prolong the lifetime of SDWN and improve the practicability of research,we rebuilt a CPP model considering the minimal transmitted power of controllers.An adaptive controller placement algorithm(ACPA)is proposed with the following two stages.First,data field method is adopted to determine sub-networks for different network topologies.Second,for each sub-network we adopt an exhaustive method to find the optimal location which meets the minimal average transmitted power to place controller.Compared with the other algorithms,the effectiveness and efficiency of the proposed scheme are validated through simulation.
文摘Shunt capacitors are broadly applied in distribution systems to scale down power losses, improve voltage profile and boost system capacity. The amount of capacitors added and location of deployment in the system highly determine the advantage of compensation. A novel global harmony search(GHS) algorithm in parallel with the backward/ forward sweep power flow technique and radial harmonic power flow was used to investigate the optimal placement and sizing of capacitors in radial distribution networks for minimizing power loss and total cost by taking account load unbalancing, mutual coupling and harmonics. The optimal capacitor placement outcomes show that the GHS algorithm can reduce total power losses up to 60 k W and leads to more than 18% of cost saving. The results also demonstrate that the GHS algorithm is more effective in minimization of power loss and total costs compared with genetic algorithm(GA), particle swarm optimization(PSO) and harmony search(HS) algorithm. Moreover, the proposed algorithm converges within 800 iterations and is faster in terms of computational time and gives better performance in finding optimal capacitor location and size compared with other optimization techniques.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60973027)Science Projects of China National Ministry of Information Industry(Grant No.01XK230009)
文摘To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.
文摘The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.
基金Supported of Project of Fok Ying Tong Education Foundation(No.104030)Supported of Key Project of National Natural Science of Foundation of China(No.70531020)+2 种基金Supported of Project of New Century Excellent Talent(No.NCET-06-0382)Supported of Key Project of Education Ministry of China(No.306023)Supported of Project of Doctoral Education(20070247075)
文摘We present a novel paradigm of sensor placement concerning data precision and estimation.Multiple abstract sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network.These sensors can cooperate with each other to obtain a precise estimate of the quantity in a real-time manner.We consider a problem on planning a minimum-cost scheme of sensor placement with desired data precision and resource consumption.Measured data is modeled as a Gaussian random variable with a changeable variance.A gird model is used to approximate the problem.We solve the problem with a heuristic algorithm using branch-and-bound method and tabu search.Our experiments demonstrate that the algorithm is correct in a certain tolerance,and it is also efficient and scalable.
文摘Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to control action and a real coded genetic algorithm then proposed to produce a global optimum solution, and proves the feasibility and advantages of this algorithm with the example of a standard test function and a two collocated actuators/sensors cantilever, and comparing the results with those given in the literatures.
文摘In this paper a new method has been proposed to determine optimal location and best setting of Thyristor Controlled Series Compensator (TCSC). Seeking the best place is performed using the sensitivity analysis and optimum setting of TCSC is managed using the genetic algorithm. The configuration of a typical TCSC from a steady-state perspective is the fixed capacitor with a thyristor controlled reactor (TCR). The effect of TCSC on the network can be modeled as a controllable reactance inserted in the related transmission line. This paper employs the DIgSILENT simulator and the DPL as a programming tool of the DIgSILENT to show the validity of the proposed method. The effectiveness of sug-gested approach has been tested on IEEE 14-bus system.
文摘In this paper, we analyse the deployment of middlebox. For a given network information and policy requirements, an attempt is made to determine the optimal location of middlebox to achieve the best performance. In terms of the end-to-end delay as a performance optimization index, a distributed middlebox placement algorithm based on potential game is proposed. Through extensive simulations, it demonstrates that the proposed algorithm achieves the near-optimal solution, and the end-to-end delay decreases significantly.
文摘Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.
文摘Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.
