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A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Dependent Tasks in Grid Computing

机译:截止日期和预算约束成本时间优化算法,用于在网格计中调度相关任务

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Computational grid has a promising future in large-scale computing, because it enables the sharing of widely distributed computing resources. Good managements with excellent scheduling algorithms are in great demand to take full advantage of it. Many scheduling algorithms in grid computing are for independent tasks. However, communications are very common in scientific computing programs. In this paper, we will propose an easy-implemented algorithm to schedule the tasks with some communications. Our algorithm is suitable for a large proportion of scientific computing programs, and is based on Binary Integer Programming. It is able to meet the users quality of service (QoS) requirements, and to minimize the combination of costs and time consumed by the users programs. We will give an example of scheduling a typical scientific computing task to show the power of our algorithm. In our experiment, the grid resource consists of an SGI Onyx 3900 supercomputer, four SGI Octane workstations, four Intel P4-2.0GHz PCs and four Intel P4-1.8GHz PCs.
机译:计算网格在大型计算中具有有希望的未来,因为它使得能够共享广泛分布的计算资源。具有优异的调度算法的良好管理是充分利用它的需求。网格计算中的许多调度算法用于独立任务。然而,通信在科学计算计划中非常常见。在本文中,我们将提出一种易于实现的算法来安排一些通信的任务。我们的算法适用于大量科学计算程序,并基于二进制整数编程。它能够满足用户服务质量(QoS)要求,并最大限度地减少用户程序消耗的成本和时间的组合。我们将举例说明典型的科学计算任务来显示我们算法的力量。在我们的实验中,网格资源包括SGI Onyx 3900超级计算机,四个SGI辛烷值工作站,四个英特尔P4-2.0GHz PC和四个英特尔P4-1.8GHz PC。

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