A mathematical model, heuristic, and simulation study for a basic data staging problem in a heterogeneous networking environment

Min Tan, M. Theys, H. Siegel, N. Beck, M. Jurczyk
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引用次数: 31

Abstract

Data staging is an important data management problem for a distributed heterogeneous networking environment, where each data storage location and intermediate node may have specific data available, storage limitations, and communication links. Sites in the network request data items and each item is associated with a specific deadline and priority. It is assumed that not all requests can be satisfied by their deadline. The work concentrates on solving a basic version of the data staging problem in which all parameter values for the communication system and the data request information represent the best known information collected so far and stay fixed throughout the scheduling process. A mathematical model for the basic data staging problem is introduced. Then, a multiple-source shortest-path algorithm based heuristic for finding a suboptimal schedule of the communication steps for data staging is presented. A simulation study is provided, which evaluates the performance of the proposed heuristic. The results show the advantages of the proposed heuristic over two random based scheduling techniques. This research, based on the simplified static model, serves as a necessary step toward solving the more realistic and complicated version of the data staging problem involving dynamic scheduling, fault tolerance, and determining where to stage data.
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异构网络环境中基本数据分段问题的数学模型、启发式和仿真研究
数据分段是分布式异构网络环境中的一个重要数据管理问题,其中每个数据存储位置和中间节点可能具有特定的可用数据、存储限制和通信链路。网络中的站点请求数据项,每个项都与特定的截止日期和优先级相关联。假定并非所有请求都能在截止日期前得到满足。该工作集中于解决数据分段问题的基本版本,其中通信系统的所有参数值和数据请求信息表示迄今为止收集的最已知信息,并在整个调度过程中保持固定。介绍了基本数据分期问题的数学模型。然后,提出了一种基于多源最短路径算法的启发式算法,用于寻找数据分段通信步骤的次优调度。通过仿真研究,对所提启发式算法的性能进行了评价。结果表明,该方法优于两种随机调度方法。本研究基于简化的静态模型,是解决更现实、更复杂的数据分期问题的必要步骤,该问题涉及动态调度、容错和确定数据分期的位置。
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