基于蚁群理论的数据源和查询处理站点的自主排序和表征

Eliana Valenzuela Andrade, Manuel Rodiguez-Martinez
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引用次数: 1

摘要

针对分布式数据库系统中数据源和查询处理站点的特征发现和排序问题,提出了一种新的方法。我们将网络建模为一个图,其中节点表示数据源和查询处理站点,其中一些可能被复制。我们引入了一种启发蚁群理论的启发式技术来动态地发现、评估和编目每个数据源或查询处理站点。我们的目标是找到访问最高质量站点提供的计算资源或数据的可能路径,并定义这些站点和数据源的质量。质量的概念可以根据性能、新鲜度、完整性或其他指标来定义。我们使用Java CSIM对该系统进行了仿真,并进行了初步的性能和新鲜度研究,旨在分析蚁群算法找到的路径的质量和新鲜度估计器的准确性。这些实验表明,我们的方法是有承诺的,并且可以比我们期望的工作提供系统需要的信息来优化中间件系统中的查询请求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomic Ranking  and Characterization of Data Sources and Query Processing Sites Using Ant Colony Theory
This paper presents a novel approach to the problem of discovering and ranking the characteristics of the data sources and query processing sites in a distributed database system. We model the network as a graph with nodes representing data sources and query processing sites, some of which might be replicated.We introduce a heuristic technique inspired in Ant Colony Theory to dynamically discover,assess and catalog each data source or query-processing site. Our goal is to find possible paths to access the computational resources or data provided by the highest quality sites and define the quality of this sites and data sources. The concept of quality could be defined  in terms of performance, freshness, completeness or other metrics. We describe a simulation of the system using Java CSIM and also a preliminary performance and freshness studies designed to analyze the quality of paths found by the Ant Colony algorithm and the accurate of the freshness estimators. These experiments show  that our approach  is promissory and could do the job than we expect offering the information that the system needs to optimize a query request in a middleware system.
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