为位置透明的调度网格需求提供光路和计算资源

Hong-Ha Nguyen, Mohan Gurusamy, Luying Zhou
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引用次数: 8

摘要

在本文中,我们定义了一个新的问题,即为一组位置透明的调度网格需求提供光路和计算资源。位置透明的调度网格需求只指定在指定时间间隔内处理输入数据所需的计算资源数量。产生需求的网络节点称为客户端节点。有几个网络节点有足够的资源来满足一个需求。这些节点称为资源节点。通过算法选择资源节点,预留一定数量的计算资源,并在资源节点和客户端节点之间提供光路。给定一组位置透明的调度网格需求,要求为每个需求提供在指定时间间隔内可用的最佳光路(即波长资源)和计算资源,以优化某个目标函数。在我们的工作中,我们开发了2个目标函数的整数线性规划(ILP)公式:1)给定网络容量,最大化可接受的需求数量;2)最小化波长链路的总数,以满足给定的一组需求。由于ILP算法的计算成本很高,我们还开发了启发式算法来处理大型网络。仿真结果表明,我们的启发式算法取得了良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Provisioning lightpaths and computing resources for location-transparent scheduled grid demands
In this paper, we define a new problem of provisioning lightpaths and computing resources for a set of location- transparent scheduled grid demands in optical grid networks. A location-transparent scheduled grid demand specifies only an amount of computing resources needed in a specified time interval to process input data. The network node generating a demand is called a client node. There are several network nodes which have sufficient resources for a demand. These nodes are called resource nodes. An algorithm is used to choose a resource node to reserve a specified amount of computing resources and provision a lightpath between the resource node and the client node. Given a set of location-transparent scheduled grid demands, it is required to provision the best lightpath (i.e. wavelength resources) as well as computing resources available during the specified time interval for each demand so as to optimize a certain objective function. In our work, we develop integer linear programming (ILP) formulations for 2 objective functions: 1) Given a network capacity, maximize the number of demands accepted; 2) Minimize the total number of wavelength-links to honor a given set of demands. Because the ILP algorithms are computationally expensive, we also develop heuristics to deal with large networks. The simulation results show that our heuristics achieve good performance.
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