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Autonomic Ranking#x0A0;#x0A0;and Characterization of Data Sources and Query Processing Sites Using Ant Colony Theory

机译:使用蚁群理论的数据源和查询处理网站的自主排名和特征

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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.
机译:本文介绍了在分布式数据库系统中发现和排列数据源和查询处理站点的问题的问题的新方法。我们将网络塑造为具有表示数据源和查询处理站点的节点的图表,其中一些可能被复制。我们在蚁群理论中引入了一种启发式技术,以动态发现,评估和编程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,并定义本网站和数据源的质量。质量的概念可以在性能,新鲜度,完整性或其他指标方面定义。我们描述了使用Java CSIM的系统的模拟,以及初步性能和新鲜度研究,旨在分析蚁群算法发现的路径质量和新鲜度估计的准确性。这些实验表明,我们的方法是原因,可以做到这项工作,而不是我们预期提供系统需要在中间件系统中优化查询请求的信息。

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