In order to avoid severe performance degradation led by the inter-cell interference (ICI) in orthogonal frequency division multiple access (OFDMA) systems with a frequency reused factor (FRF) of 1,distributed schedule...In order to avoid severe performance degradation led by the inter-cell interference (ICI) in orthogonal frequency division multiple access (OFDMA) systems with a frequency reused factor (FRF) of 1,distributed schedule algorithm (DS-OCS) and distributed proportional fairness schedule algorithm (DPFS-OCS) based on orthogonal complement space (OCS) were proposed. The first right and left singular vectors of the channel that the user experienced were selected as the transmitting and receiving beamforming vectors. An interference space was spanned by the left singular vectors of the entire interference users in the same channel. The most suitable user lay in the OCS of the interference space was scheduled to avoid suffering interference from neighboring cells based on the criterion of system capacity maximizing and proportional fairness. The simulation results show that the average system capacity can be improved by 2%-4% compared with the DS-OCS algorithm with the Max C/I algorithm,by 6%-10% compared with the DPFS-OCS algorithm with the PF algorithm.展开更多
In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic h...In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.展开更多
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
This study presents a novel integrated framework for autonomous vehicle control at unsignalized intersections in mixed traffic environments,addressing the critical challenge of coordinating Society of Automotive Engin...This study presents a novel integrated framework for autonomous vehicle control at unsignalized intersections in mixed traffic environments,addressing the critical challenge of coordinating Society of Automotive Engineers(SAE)level 4 connected and autonomous vehicles(CAVs)and manually driven vehicles(MVs).The combination of driving intention prediction with a Social Long Short-Term Memory(Social LSTM)and a scheduling algorithm with optimization-driven Pass-through Time Windows(PTWs)is adopted to address traffic flow uncertainty.The Social LSTM model with spatial pooling layers to capture complex multi-vehicle interactions and predict surrounding vehicles’trajectories and maneuver intentions using naturalistic driving data from the CitySim dataset was applied.Unlike conventional approaches that treat prediction and control separately,this framework leverages high-confidence trajectory predictions to inform proactive scheduling decisions for conflict mitigation.The PTW scheduling algorithm formulates intersection management as a constrained optimization problem,dynamically allocating non-overlapping temporal windows for vehicle entering and exiting while considering vehicle dynamics,safety gaps,and deceleration constraints.Comprehensive simulation analysis across varying traffic volumes and CAV market penetration rates reveals significant improvements in both safety and operational efficiency.The scheduling algorithm has notably reduced traffic delay times while maintaining balance with safety measures.This finding provides a fundamental basis for infrastructure-based cooperative driving research,serving as a contributing factor for the development of advanced traffic management systems during the mixed-traffic period.展开更多
One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consider...One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.展开更多
Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and th...Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.展开更多
In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop pro...In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.展开更多
In the dynamic, complex and unbounded Grid systems, failures of Grid resources caused by malicious attacks and hardware failures are inevitable and have an adverse effect on the execution of tasks. To mitigate this pr...In the dynamic, complex and unbounded Grid systems, failures of Grid resources caused by malicious attacks and hardware failures are inevitable and have an adverse effect on the execution of tasks. To mitigate this problem, a makespan and reliability driven (MRD) sufferage scheduling algorithm is designed and implemented. Different from the traditional Grid scheduling algorithms, the algorithm addresses the makespan as well as reliability of tasks. The simulation experimental results show that the MRD sufferage scheduling algorithm can increase reliability of tasks and can trade off reliability against makespan of tasks by adjusting the weighting parameter in its cost function. So it can be applied to the complex Grid computing environment well.展开更多
This paper considers a reentrant scheduling problem on parallel primary machines with a remote server machine, which is required to carry out the setup operation. In this problem, each job has three operations. The fi...This paper considers a reentrant scheduling problem on parallel primary machines with a remote server machine, which is required to carry out the setup operation. In this problem, each job has three operations. The first and last operations are performed by the same primary machine, implying the reentrance, and the second operation is processed on the single server machine. The order of jobs is predetermined in our context. The challenge is to assign jobs to the primary machines to minimize the makespan. We develop a genetic algorithm(GA) to solve this problem. Based on a simple strategy of assigning jobs in batches on the parallel primary machines, the standardized random key vector representation is employed to split the jobs into batches. Comparisons among the proposed algorithm, the branch and bound(BB) algorithm and the heuristic algorithm, coordinated scheduling(CS), which is only one heuristic algorithm to solve this problem in the literature, are made on the benchmark data. The computational experiments show that the proposed genetic algorithm outperforms the heuristic CS and the maximum relative improvement rate in the makespan is 1.66%.展开更多
In response to the production capacity and functionality variations, a genetic algorithm (GA) embedded with deterministic timed Petri nets(DTPN) for reconfigurable production line(RPL) is proposed to solve its s...In response to the production capacity and functionality variations, a genetic algorithm (GA) embedded with deterministic timed Petri nets(DTPN) for reconfigurable production line(RPL) is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.展开更多
It is important to evaluate function behaviors and performance features of task scheduling algorithm in the multi-processor system.A novel dynamic measurement method(DMM)was proposed to measure the task scheduling alg...It is important to evaluate function behaviors and performance features of task scheduling algorithm in the multi-processor system.A novel dynamic measurement method(DMM)was proposed to measure the task scheduling algorithm’s correctness and dependability.In a multi-processor system,task scheduling problem is represented by a combinatorial evaluation model,interactive Markov chain(IMC),and solution space of the algorithm with time and probability metrics is described by action-based continuous stochastic logic(aCSL).DMM derives a path by logging runtime scheduling actions and corresponding times.Through judging whether the derived path can be received by task scheduling IMC model,DMM analyses the correctness of algorithm.Through judging whether the actual values satisfy label function of the initial state,DMM analyses the dependability of algorithm.The simulation shows that DMM can effectively characterize the function behaviors and performance features of task scheduling algorithm.展开更多
The sharing of operation and management information is required by smart grid.The amount of information transmitted in electric power communication systems will increase greatly in the near future.The integrated infor...The sharing of operation and management information is required by smart grid.The amount of information transmitted in electric power communication systems will increase greatly in the near future.The integrated information transmission technology is an important method for transmitting various kinds of information via the existing broadband channels and networks in power systems.To implement integrated information transmission in power systems,the problem about how to guarantee the quality of service(QoS)of the communication services must be dealt with.展开更多
This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage ti...This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problem is NP-hard and the problem size is exponentially large for a realistic-sized problem. Therefore,we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithm averagely outperforms ant colony optimization and Tabu search with slightly longer computational time.展开更多
This letter presents an efficient scheduling algorithm DTRR (Dual-Threshold Round Robin) for input-queued switches. In DTRR, a new matched input and output by round robin in a cell time will be locked by two self-adap...This letter presents an efficient scheduling algorithm DTRR (Dual-Threshold Round Robin) for input-queued switches. In DTRR, a new matched input and output by round robin in a cell time will be locked by two self-adaptive thresholds whenever the queue length or the wait-time of the head cell in the corresponding Virtual Output Queue (VOQ) exceeds the thresholds. The locked input and output will be matched directly in the succeeding cell time until they are unlocked. By employing queue length and wait-time thresholds which are updated every cell time simultane- ously, DTRR achieves a good tradeoff between the performance and hardware complexity. Simula- tion results indicate that the delay performance of DTRR is competitive compared to other typical scheduling algorithms under various traffic patterns especially under diagonal traffic.展开更多
The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications.These switching fabrics are efficiently driven by the deployed scheduling algorithms...The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications.These switching fabrics are efficiently driven by the deployed scheduling algorithms.In this paper,we proposed two scheduling algorithms for input queued switches whose operations are based on ranking procedures.At first,we proposed a Simple 2-Bit(S2B)scheme which uses binary ranking procedure and queue size for scheduling the packets.Here,the Virtual Output Queue(VOQ)set with maximum number of empty queues receives higher rank than other VOQ’s.Through simulation,we showed S2B has better throughput performance than Highest Ranking First(HRF)arbitration under uniform,and non-uniform traffic patterns.To further improve the throughput-delay performance,an Enhanced 2-Bit(E2B)approach is proposed.This approach adopts an integer representation for rank,which is the number of empty queues in a VOQ set.The simulation result shows E2B outperforms S2B and HRF scheduling algorithms with maximum throughput-delay performance.Furthermore,the algorithms are simulated under hotspot traffic and E2B proves to be more efficient.展开更多
Chip multiprocessors(CMPs) allow thread level parallelism,thus increasing performance.However,this comes with the cost of temperature problem.CMPs require more power,creating non uniform power map and hotspots.Aiming ...Chip multiprocessors(CMPs) allow thread level parallelism,thus increasing performance.However,this comes with the cost of temperature problem.CMPs require more power,creating non uniform power map and hotspots.Aiming at this problem,a thread scheduling algorithm,the greedy scheduling algorithm,was proposed to reduce the thermal emergencies and to improve the throughput.The greedy scheduling algorithm was implemented in the Linux kernel on Intel's Quad-Core system.The experimental results show that the greedy scheduling algorithm can reduce 9.6%-78.5% of the hardware dynamic thermal management(DTM) in various combinations of workloads,and has an average of 5.2% and up to 9.7% throughput higher than the Linux standard scheduler.展开更多
Multiple QoS modeling and algorithm in grid system is considered.Grid QoS requirements can be formulated as a utility function for each task as a weighted sum of its each dimensional QoS utility functions.Multiple QoS...Multiple QoS modeling and algorithm in grid system is considered.Grid QoS requirements can be formulated as a utility function for each task as a weighted sum of its each dimensional QoS utility functions.Multiple QoS constraint resource scheduling optimization in computational grid is distributed to two subproblems:optimization of grid user and grid resource provider.Grid QoS scheduling can be achieved by solving sub problems via an iterative algorithm.展开更多
We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider...We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider the dynamically arrival model of disk requests to obtain an algorithm, shortest path first-fit first (SPFF). This algorithm is based on the shortest path of disk head motion constructed by all the pendent requests. From view of the head moving distance, it has the stronger glohality than SSTF. From view of the head-moving direction, it has the better flexibility than SCAN. Therefore, SPFF keeps the advantage of SCAN and, at the same time, absorbs the strength of SSTF. The algorithm SPFF not only shows the more superiority than other scheduling polices, but also have higher adjustability to meet the computer system's different demands.展开更多
Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm (TDSA). The algorithm adopts the throughput of cluster back-ends to evaluate their load...Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm (TDSA). The algorithm adopts the throughput of cluster back-ends to evaluate their load and employs the neural network model to predict the future load so that the scheduling system features a self-learning capability and good adaptability to the change of load. Moreover, it separates static requests from dynamic requests to make full use of the CPU resources and takes the locality of requests into account to improve the cache hit ratio. Experimental re suits from the testing tool of WebBench^TM show better per formance for Web cluster server with TDSA than that with traditional scheduling algorithms.展开更多
As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based ...As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based intensive data processing. For modern disks, increase of disk rotation rate makes overhead of disk access to data transfer heavier. Therefore, it seems more important to improve both parallel processing capability of disk I/O and disk-scheduling performance at the same time. For disk-scheduling algorithms based on both disk arm and rotational positions, their time-resolving powers are more precise in comparison with those for disk-scheduling algorithms based only on disk arm position. Algorithms of this sort are studied in this paper. Several improved algorithms based on rotational position are proposed, and simulation results of their performances demonstrate.展开更多
基金Projects(2009ZX03003-003, 2009ZX03003-004) supported by the Major National Science & Technology ProgramProject(B08038) supported by the "111" Project+1 种基金Project(HX0109012417) supported by Huawei Technologies Co., Ltd, ChinaProject(IRT0852) supported by Program for Changjiang Scholars and Innovative Research Team in Chinese University
摘要In order to avoid severe performance degradation led by the inter-cell interference (ICI) in orthogonal frequency division multiple access (OFDMA) systems with a frequency reused factor (FRF) of 1,distributed schedule algorithm (DS-OCS) and distributed proportional fairness schedule algorithm (DPFS-OCS) based on orthogonal complement space (OCS) were proposed. The first right and left singular vectors of the channel that the user experienced were selected as the transmitting and receiving beamforming vectors. An interference space was spanned by the left singular vectors of the entire interference users in the same channel. The most suitable user lay in the OCS of the interference space was scheduled to avoid suffering interference from neighboring cells based on the criterion of system capacity maximizing and proportional fairness. The simulation results show that the average system capacity can be improved by 2%-4% compared with the DS-OCS algorithm with the Max C/I algorithm,by 6%-10% compared with the DPFS-OCS algorithm with the PF algorithm.
基金funding from the European Commission by the Ruralities project(grant agreement no.101060876).
摘要In this paper,we propose a new privacy-aware transmission scheduling algorithm for 6G ad hoc networks.This system enables end nodes to select the optimum time and scheme to transmit private data safely.In 6G dynamic heterogeneous infrastructures,unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy.Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service(QoS).As the transport network is built of ad hoc nodes,there is no guarantee about their trustworthiness or behavior,and transversal functionalities are delegated to the extreme nodes.However,while security can be guaranteed in extreme-to-extreme solutions,privacy cannot,as all intermediate nodes still have to handle the data packets they are transporting.Besides,traditional schemes for private anonymous ad hoc communications are vulnerable against modern intelligent attacks based on learning models.The proposed scheme fulfills this gap.Findings show the probability of a successful intelligent attack reduces by up to 65%compared to ad hoc networks with no privacy protection strategy when used the proposed technology.While congestion probability can remain below 0.001%,as required in 6G services.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
摘要In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金supported by the Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure and Transport(Grant RS-2022-00142565)supported by National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2022R1A2C1093424).
摘要This study presents a novel integrated framework for autonomous vehicle control at unsignalized intersections in mixed traffic environments,addressing the critical challenge of coordinating Society of Automotive Engineers(SAE)level 4 connected and autonomous vehicles(CAVs)and manually driven vehicles(MVs).The combination of driving intention prediction with a Social Long Short-Term Memory(Social LSTM)and a scheduling algorithm with optimization-driven Pass-through Time Windows(PTWs)is adopted to address traffic flow uncertainty.The Social LSTM model with spatial pooling layers to capture complex multi-vehicle interactions and predict surrounding vehicles’trajectories and maneuver intentions using naturalistic driving data from the CitySim dataset was applied.Unlike conventional approaches that treat prediction and control separately,this framework leverages high-confidence trajectory predictions to inform proactive scheduling decisions for conflict mitigation.The PTW scheduling algorithm formulates intersection management as a constrained optimization problem,dynamically allocating non-overlapping temporal windows for vehicle entering and exiting while considering vehicle dynamics,safety gaps,and deceleration constraints.Comprehensive simulation analysis across varying traffic volumes and CAV market penetration rates reveals significant improvements in both safety and operational efficiency.The scheduling algorithm has notably reduced traffic delay times while maintaining balance with safety measures.This finding provides a fundamental basis for infrastructure-based cooperative driving research,serving as a contributing factor for the development of advanced traffic management systems during the mixed-traffic period.
基金supported by Scientific Research Foundation for the Returned Overseas Chinese ScholarsState Education Ministry under Grant No.2010-2011 and Chinese Post-doctoral Research Foundation
摘要One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.
摘要Dynamic exclusive pickup and delivery problem with time windows (DE-PDPTW), aspecial dynamic vehicle scheduling problem, is proposed. Its mathematical description is given andits static properties are analyzed, and then the problem is simplified asthe asymmetrical travelingsalesman problem with time windows. The rolling horizon scheduling algorithm (RHSA) to solve thisdynamic problem is proposed. By the rolling of time horizon, the RHSA can adapt to the problem'sdynamic change and reduce the computation time by dealing with only part of the customers in eachrolling time horizon. Then, its three factors, the current customer window, the scheduling of thecurrent customer window and the rolling strategy, are analyzed. The test results demonstrate theeffectiveness of the RHSA to solve the dynamic vehicle scheduling problem.
基金supported by the National Key R&D Plan(2020YFB1712902)the National Natural Science Foundation of China(52075036).
摘要In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.
摘要In the dynamic, complex and unbounded Grid systems, failures of Grid resources caused by malicious attacks and hardware failures are inevitable and have an adverse effect on the execution of tasks. To mitigate this problem, a makespan and reliability driven (MRD) sufferage scheduling algorithm is designed and implemented. Different from the traditional Grid scheduling algorithms, the algorithm addresses the makespan as well as reliability of tasks. The simulation experimental results show that the MRD sufferage scheduling algorithm can increase reliability of tasks and can trade off reliability against makespan of tasks by adjusting the weighting parameter in its cost function. So it can be applied to the complex Grid computing environment well.
基金Supported by National Natural Science Foundation of China(No.61271374)Beijing Natural Science Foundation(No.4122068)
摘要This paper considers a reentrant scheduling problem on parallel primary machines with a remote server machine, which is required to carry out the setup operation. In this problem, each job has three operations. The first and last operations are performed by the same primary machine, implying the reentrance, and the second operation is processed on the single server machine. The order of jobs is predetermined in our context. The challenge is to assign jobs to the primary machines to minimize the makespan. We develop a genetic algorithm(GA) to solve this problem. Based on a simple strategy of assigning jobs in batches on the parallel primary machines, the standardized random key vector representation is employed to split the jobs into batches. Comparisons among the proposed algorithm, the branch and bound(BB) algorithm and the heuristic algorithm, coordinated scheduling(CS), which is only one heuristic algorithm to solve this problem in the literature, are made on the benchmark data. The computational experiments show that the proposed genetic algorithm outperforms the heuristic CS and the maximum relative improvement rate in the makespan is 1.66%.
基金This project is supported by Key Science-Technology Project of Shanghai City Tenth Five-Year-Plan, China (No.031111002)Specialized Research Fund for the Doctoral Program of Higher Education, China (No.20040247033)Municipal Key Basic Research Program of Shanghai, China (No.05JC14060)
摘要In response to the production capacity and functionality variations, a genetic algorithm (GA) embedded with deterministic timed Petri nets(DTPN) for reconfigurable production line(RPL) is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.
基金the National Natural Science Foundation of China(Nos.11371003 and 11461006)the Special Fund for Scientific and Technological Bases and Talents of Guangxi(No.2016AD05050)+3 种基金the Special Fund for Bagui Scholars of Guangxithe Major Tendering Project of the National Social Science Foundation(No.17ZDA160)the Sichuan Science and Technology Project(No.19YYJC0038)the Fundamental Research Funds for the Central Universities,SWUN(No.2019NYB20)
摘要It is important to evaluate function behaviors and performance features of task scheduling algorithm in the multi-processor system.A novel dynamic measurement method(DMM)was proposed to measure the task scheduling algorithm’s correctness and dependability.In a multi-processor system,task scheduling problem is represented by a combinatorial evaluation model,interactive Markov chain(IMC),and solution space of the algorithm with time and probability metrics is described by action-based continuous stochastic logic(aCSL).DMM derives a path by logging runtime scheduling actions and corresponding times.Through judging whether the derived path can be received by task scheduling IMC model,DMM analyses the correctness of algorithm.Through judging whether the actual values satisfy label function of the initial state,DMM analyses the dependability of algorithm.The simulation shows that DMM can effectively characterize the function behaviors and performance features of task scheduling algorithm.
摘要The sharing of operation and management information is required by smart grid.The amount of information transmitted in electric power communication systems will increase greatly in the near future.The integrated information transmission technology is an important method for transmitting various kinds of information via the existing broadband channels and networks in power systems.To implement integrated information transmission in power systems,the problem about how to guarantee the quality of service(QoS)of the communication services must be dealt with.
基金Thailand Research Fund (Grant #MRG5480176)National Research University Project of Thailand Office of Higher Education Commission
摘要This paper considers a scheduling problem in industrial make-and-pack batch production process. This process equips with sequence-dependent changeover time, multipurpose storage units with limited capacity, storage time, batch splitting, partial equipment connectivity and transfer time. The objective is to make a production plan to satisfy all constraints while meeting demand requirement of packed products from various product families. This problem is NP-hard and the problem size is exponentially large for a realistic-sized problem. Therefore,we propose a genetic algorithm to handle this problem. Solutions to the problems are represented by chromosomes of product family sequences. These sequences are decoded to assign the resource for producing packed products according to forward assignment strategy and resource selection rules. These techniques greatly reduce unnecessary search space and improve search speed. In addition, design of experiment is carefully utilized to determine appropriate parameter settings. Ant colony optimization and Tabu search are also implemented for comparison. At the end of each heuristics, local search is applied for the packed product sequence to improve makespan. In an experimental analysis, all heuristics show the capability to solve large instances within reasonable computational time. In all problem instances, genetic algorithm averagely outperforms ant colony optimization and Tabu search with slightly longer computational time.
基金Supported by the National Natural Science Foundation of China (No.60472057).
摘要This letter presents an efficient scheduling algorithm DTRR (Dual-Threshold Round Robin) for input-queued switches. In DTRR, a new matched input and output by round robin in a cell time will be locked by two self-adaptive thresholds whenever the queue length or the wait-time of the head cell in the corresponding Virtual Output Queue (VOQ) exceeds the thresholds. The locked input and output will be matched directly in the succeeding cell time until they are unlocked. By employing queue length and wait-time thresholds which are updated every cell time simultane- ously, DTRR achieves a good tradeoff between the performance and hardware complexity. Simula- tion results indicate that the delay performance of DTRR is competitive compared to other typical scheduling algorithms under various traffic patterns especially under diagonal traffic.
摘要The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications.These switching fabrics are efficiently driven by the deployed scheduling algorithms.In this paper,we proposed two scheduling algorithms for input queued switches whose operations are based on ranking procedures.At first,we proposed a Simple 2-Bit(S2B)scheme which uses binary ranking procedure and queue size for scheduling the packets.Here,the Virtual Output Queue(VOQ)set with maximum number of empty queues receives higher rank than other VOQ’s.Through simulation,we showed S2B has better throughput performance than Highest Ranking First(HRF)arbitration under uniform,and non-uniform traffic patterns.To further improve the throughput-delay performance,an Enhanced 2-Bit(E2B)approach is proposed.This approach adopts an integer representation for rank,which is the number of empty queues in a VOQ set.The simulation result shows E2B outperforms S2B and HRF scheduling algorithms with maximum throughput-delay performance.Furthermore,the algorithms are simulated under hotspot traffic and E2B proves to be more efficient.
基金Projects(2009AA01Z124,2009AA01Z102) supported by the National High Technology Research and Development Program of ChinaProjects(60970036,61076025) supported by the National Natural Science Foundation of China
摘要Chip multiprocessors(CMPs) allow thread level parallelism,thus increasing performance.However,this comes with the cost of temperature problem.CMPs require more power,creating non uniform power map and hotspots.Aiming at this problem,a thread scheduling algorithm,the greedy scheduling algorithm,was proposed to reduce the thermal emergencies and to improve the throughput.The greedy scheduling algorithm was implemented in the Linux kernel on Intel's Quad-Core system.The experimental results show that the greedy scheduling algorithm can reduce 9.6%-78.5% of the hardware dynamic thermal management(DTM) in various combinations of workloads,and has an average of 5.2% and up to 9.7% throughput higher than the Linux standard scheduler.
基金the National Natural Science Foundation of China(60402028,60672137)Wuhan Yonger Dawning Foundation(20045006071-15)China Specialized Research Fund for the Doctoral Program of Higher Eduction(20060497015).
摘要Multiple QoS modeling and algorithm in grid system is considered.Grid QoS requirements can be formulated as a utility function for each task as a weighted sum of its each dimensional QoS utility functions.Multiple QoS constraint resource scheduling optimization in computational grid is distributed to two subproblems:optimization of grid user and grid resource provider.Grid QoS scheduling can be achieved by solving sub problems via an iterative algorithm.
基金Supported by the National Natural Science Founda-tion of China (60373088)
摘要We put forward an optimal disk schedule with n disk requests and prove its optimality mathematically.Generalizing the idea of an optimal disk schedule, we remove the limit of n requests and, at the same time, consider the dynamically arrival model of disk requests to obtain an algorithm, shortest path first-fit first (SPFF). This algorithm is based on the shortest path of disk head motion constructed by all the pendent requests. From view of the head moving distance, it has the stronger glohality than SSTF. From view of the head-moving direction, it has the better flexibility than SCAN. Therefore, SPFF keeps the advantage of SCAN and, at the same time, absorbs the strength of SSTF. The algorithm SPFF not only shows the more superiority than other scheduling polices, but also have higher adjustability to meet the computer system's different demands.
基金Supported by the National Natural Science Funda-tion of China (60175015)
摘要Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm (TDSA). The algorithm adopts the throughput of cluster back-ends to evaluate their load and employs the neural network model to predict the future load so that the scheduling system features a self-learning capability and good adaptability to the change of load. Moreover, it separates static requests from dynamic requests to make full use of the CPU resources and takes the locality of requests into account to improve the cache hit ratio. Experimental re suits from the testing tool of WebBench^TM show better per formance for Web cluster server with TDSA than that with traditional scheduling algorithms.
基金Project supported by National Natural Science Foundation of Chi-na( Grant No . 60373088) , and Defense Pre-research Project ofChina(Grant No .413160502)
摘要As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based intensive data processing. For modern disks, increase of disk rotation rate makes overhead of disk access to data transfer heavier. Therefore, it seems more important to improve both parallel processing capability of disk I/O and disk-scheduling performance at the same time. For disk-scheduling algorithms based on both disk arm and rotational positions, their time-resolving powers are more precise in comparison with those for disk-scheduling algorithms based only on disk arm position. Algorithms of this sort are studied in this paper. Several improved algorithms based on rotational position are proposed, and simulation results of their performances demonstrate.