Description: 实现网格环境下资源调度和分配的仿真，主要由java实现，并且调用了simjava类库-The realization of grid resource scheduling and allocation of the simulation, mainly by the java to achieve, and call a class library simjava Platform: |
Size: 3446784 |
Author:lw |
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Description: 主要介绍了如何用gridsim工具进行网格资源调度的模拟-Focuses on how to use tools gridsim Simulation of Grid Resource Scheduling Platform: |
Size: 5120 |
Author:peng lijuan |
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Description: p2p思想和关键路径的网格资源调度p2p thinking and critical path of the grid resource scheduling-p2p thinking and critical path of the grid resource scheduling Platform: |
Size: 367616 |
Author:tai234 |
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Description: p2p思想和关键路径的网格资源调度p2p thinking and critical path of the grid resource scheduling-p2p thinking and critical path of the grid resource scheduling Platform: |
Size: 369664 |
Author:pip |
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Description: On the basis of author’s former work, this
paper presents an improved ant colony algorithm,
namely adaptive ant colony algorithm. In the proposed
algorithm, the value of evaporation rate ρ is adaptively
changed and a minimum value ρmin is assigned. Thereby,
the evaporation rate ρ is under control and will never be
reduced to 0. Then the paper applies the proposed
algorithm to grid task scheduling. Comparing
experimental results with the original algorithm show
that the proposed algorithm is more efficient both in task
scheduling efficiency and resource load. Platform: |
Size: 280576 |
Author:rishi |
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Description: 实现网格环境下资源调度和分配的仿真，主要由java实现，并且调用了simjava类库-The realization of grid resource scheduling and allocation of the simulation, mainly by the java to achieve, and call a class library simjava Platform: |
Size: 3387392 |
Author:刘海君 |
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Description: Abstract. In this paper, we present a scheduler for distributing workflows in Utility Management System (UMS).
The system executes a large number of workflows, which have very high resource requirements. The workflows have
different computational requirements and thus the optimization of resource utilization must be performed in a way that
is different from the standard approach of scheduling workflows. We developed a strategy for allocating workflows,
which is based on a genetic algorithm. The proposed architecture executes a scheduling algorithm by using a feedback
from the execution monitor. We also report on an experimental study, which shows that a significant improvement of
overall execution time can be achieved by using the genetic algorithm. The algorithm is used for designing effective
Grid schedulers that optimize makespan. The study further shows that the overall system (UMS) performance is
significantly improved this finding indicates that there can be reduction in hardware investment.-Abstract. In this paper, we present a scheduler for distributing workflows in Utility Management System (UMS).
The system executes a large number of workflows, which have very high resource requirements. The workflows have
different computational requirements and thus the optimization of resource utilization must be performed in a way that
is different from the standard approach of scheduling workflows. We developed a strategy for allocating workflows,
which is based on a genetic algorithm. The proposed architecture executes a scheduling algorithm by using a feedback
from the execution monitor. We also report on an experimental study, which shows that a significant improvement of
overall execution time can be achieved by using the genetic algorithm. The algorithm is used for designing effective
Grid schedulers that optimize makespan. The study further shows that the overall system (UMS) performance is
significantly improved this finding indicates that there can be reduction in hardware investment. Platform: |
Size: 172032 |
Author:nemanja |
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Description: Grid computing could be the future computing paradigm for enterprise applications, one of its benefits being that it
can be used for executing large scale applications. Utility Management Systems execute very large numbers of
workflows with very high resource requirements. This paper proposes architecture for a new scheduling mechanism
that dynamically executes a scheduling algorithm using feedback about the current status Grid nodes. Two
Artificial Neural Networks were created in order to solve the scheduling problem. A case study is created for the
Meter Data Management system with measurements from the Smart Metering system for the city of Novi Sad,
Serbia. Performance tests show that significant improvement of overall execution time can be achieved by
Hierarchical Artificial Neural Networks. Platform: |
Size: 679936 |
Author:nemanja |
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Search - resource scheduling grid