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 Q...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
To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated ...To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.展开更多
A general scheduling framework (GSF) for independent tasks in computational Grid is proposed in this paper, which modeled by Petri net and located on the layer of Grid scheduler. Furthermore, a new mapping algorithm a...A general scheduling framework (GSF) for independent tasks in computational Grid is proposed in this paper, which modeled by Petri net and located on the layer of Grid scheduler. Furthermore, a new mapping algorithm aimed at time and cost is designed on the basis of this framework. The algorithm uses weighted average fuzzy applicability to express the matching degree between available machines and independent tasks. Some existent heuristic algorithms are tested in GSF, and the results of simulation and comparison not only show good flexibility and adaptability of GSF, but also prove that, given a certain aim, the new algorithm can consider the factors of time and cost as a whole and its performance is higher than those mentioned algorithms.展开更多
The computational grid provides a promising platform for the deployment of various high-performance computing applications. A grid system consists of heterogeneous resource domains, while the computational tasks of fi...The computational grid provides a promising platform for the deployment of various high-performance computing applications. A grid system consists of heterogeneous resource domains, while the computational tasks of finite element analysis may differ in demand of computing power. The cost-effective utilization of resources in the grid can be obtained through scheduling tasks to optimal resource domains. Firstly, a cost-effective scheduling strategy is presented for finite element applications. Secondly, aiming at the conjugate gradient solver stemming from finite element analysis, a performance evaluation formula is presented for determining optimal resouree domains, which is derived from phase parallel model and takes the heterogeneous characteristic of resource domains into account. Finally, experimental results show that the presented formula delivers a good estimation of the actual execution time, and indicate that the presented formula can be used to determine optimal resource domains in the grid environment.展开更多
Algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes a DAG task scheduling model used in grid computing environment, secondly discusses generational schedu...Algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes a DAG task scheduling model used in grid computing environment, secondly discusses generational scheduling (GS) and communication inclusion generational scheduling (CIGS) algorithms. Finally, an improved CIGS algorithm is proposed to use in grid computing environment, and it has been proved effectively.展开更多
Task scheduling is one of the core steps to effectively exploit the capabilities of heterogeneous re-sources in the grid.This paper presents a new hybrid differential evolution(HDE)algorithm for findingan optimal or n...Task scheduling is one of the core steps to effectively exploit the capabilities of heterogeneous re-sources in the grid.This paper presents a new hybrid differential evolution(HDE)algorithm for findingan optimal or near-optimal schedule within reasonable time.The encoding scheme and the adaptation ofclassical differential evolution algorithm for dealing with discrete variables are discussed.A simple but ef-fective local search is incorporated into differential evolution to stress exploitation.The performance of theproposed HDE algorithm is showed by being compared with a genetic algorithm(GA)on a known staticbenchmark for the problem.Experimental results indicate that the proposed algorithm has better perfor-mance than GA in terms of both solution quality and computational time,and thus it can be used to de-sign efficient dynamic schedulers in batch mode for real grid systems.展开更多
In this paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing hybrid algorithm （PGSAHA） and applied to solve task scheduling problem i...In this paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing hybrid algorithm （PGSAHA） and applied to solve task scheduling problem in grid computing. It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively. When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.展开更多
The MAC layer in IEEE802.16 is designed to differentiate service among traffic categories with different multimedia requirements.In this paper,a scheduling algorithm at MAC layer for multiple connections with diverse ...The MAC layer in IEEE802.16 is designed to differentiate service among traffic categories with different multimedia requirements.In this paper,a scheduling algorithm at MAC layer for multiple connections with diverse QoS requirements is proposed.As for this algorithm,each connection is assigned a priority,which is updated dynamically based on its service status concluding queue characteristic and channel state.A connection with the highest priority is scheduled each time.Analytical model is developed by assuming a Finite State Markov Chain(FSMC)channel model.Simulation results show that the proposed scheduling algorithm can improve the performance of mean waiting time and throughput in broadband wireless networks.展开更多
针对数据网格环境下的多QoS约束任务调度问题,提出了一种基于最早完成时间与QoS相识度的数据网格任务调度算法(data grid task scheduling algorithm based on Min-min and QoS similarity,MS-GTSA)。该算法将最早完成时间与S-GTSA算法...针对数据网格环境下的多QoS约束任务调度问题,提出了一种基于最早完成时间与QoS相识度的数据网格任务调度算法(data grid task scheduling algorithm based on Min-min and QoS similarity,MS-GTSA)。该算法将最早完成时间与S-GTSA算法相结合,在任务调度过程中,选取任务QoS约束与资源QoS匹配最佳,且完成时间最早的一项优先进行调度。在满足任务最佳QoS匹配的同时,时间跨度得到了较大的改善。仿真结果表明,该算法有效降低了任务调度的时间跨度,在综合性能上较S-GTSA算法有所提高。展开更多
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).
文摘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The National Natural Science Foundation of China(No60673054,90412012)
文摘To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.
基金Project (60433020) supported by the National Natural Science Foundation of China project supported by the Postdoctor-al Science Foundation of Central South University
文摘A general scheduling framework (GSF) for independent tasks in computational Grid is proposed in this paper, which modeled by Petri net and located on the layer of Grid scheduler. Furthermore, a new mapping algorithm aimed at time and cost is designed on the basis of this framework. The algorithm uses weighted average fuzzy applicability to express the matching degree between available machines and independent tasks. Some existent heuristic algorithms are tested in GSF, and the results of simulation and comparison not only show good flexibility and adaptability of GSF, but also prove that, given a certain aim, the new algorithm can consider the factors of time and cost as a whole and its performance is higher than those mentioned algorithms.
文摘The computational grid provides a promising platform for the deployment of various high-performance computing applications. A grid system consists of heterogeneous resource domains, while the computational tasks of finite element analysis may differ in demand of computing power. The cost-effective utilization of resources in the grid can be obtained through scheduling tasks to optimal resource domains. Firstly, a cost-effective scheduling strategy is presented for finite element applications. Secondly, aiming at the conjugate gradient solver stemming from finite element analysis, a performance evaluation formula is presented for determining optimal resouree domains, which is derived from phase parallel model and takes the heterogeneous characteristic of resource domains into account. Finally, experimental results show that the presented formula delivers a good estimation of the actual execution time, and indicate that the presented formula can be used to determine optimal resource domains in the grid environment.
文摘Algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes a DAG task scheduling model used in grid computing environment, secondly discusses generational scheduling (GS) and communication inclusion generational scheduling (CIGS) algorithms. Finally, an improved CIGS algorithm is proposed to use in grid computing environment, and it has been proved effectively.
基金supported by the National Basic Research Program of China(No.2007CB316502)the National Natural Science Foundation of China(No.60534060)
文摘Task scheduling is one of the core steps to effectively exploit the capabilities of heterogeneous re-sources in the grid.This paper presents a new hybrid differential evolution(HDE)algorithm for findingan optimal or near-optimal schedule within reasonable time.The encoding scheme and the adaptation ofclassical differential evolution algorithm for dealing with discrete variables are discussed.A simple but ef-fective local search is incorporated into differential evolution to stress exploitation.The performance of theproposed HDE algorithm is showed by being compared with a genetic algorithm(GA)on a known staticbenchmark for the problem.Experimental results indicate that the proposed algorithm has better perfor-mance than GA in terms of both solution quality and computational time,and thus it can be used to de-sign efficient dynamic schedulers in batch mode for real grid systems.
基金Supported by the National Basic ResearchProgramof China (973 Program2003CB314804)
文摘In this paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing hybrid algorithm （PGSAHA） and applied to solve task scheduling problem in grid computing. It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively. When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.
文摘The MAC layer in IEEE802.16 is designed to differentiate service among traffic categories with different multimedia requirements.In this paper,a scheduling algorithm at MAC layer for multiple connections with diverse QoS requirements is proposed.As for this algorithm,each connection is assigned a priority,which is updated dynamically based on its service status concluding queue characteristic and channel state.A connection with the highest priority is scheduled each time.Analytical model is developed by assuming a Finite State Markov Chain(FSMC)channel model.Simulation results show that the proposed scheduling algorithm can improve the performance of mean waiting time and throughput in broadband wireless networks.
文摘针对数据网格环境下的多QoS约束任务调度问题,提出了一种基于最早完成时间与QoS相识度的数据网格任务调度算法(data grid task scheduling algorithm based on Min-min and QoS similarity,MS-GTSA)。该算法将最早完成时间与S-GTSA算法相结合,在任务调度过程中,选取任务QoS约束与资源QoS匹配最佳,且完成时间最早的一项优先进行调度。在满足任务最佳QoS匹配的同时,时间跨度得到了较大的改善。仿真结果表明,该算法有效降低了任务调度的时间跨度,在综合性能上较S-GTSA算法有所提高。
