Self Organization in Coordination Systems Using a WordNet-Based Ontology

Danilo Pianini, Sascia Virruso, R. Menezes, Andrea Omicini, Mirko Viroli
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引用次数: 10

Abstract

In today’s data-intensive world, the need for data organization has increased dramatically. Distributed systems are dealing with unheard amounts of data arising primarily from the popularization of pervasive computing applications and the so-called “data-in-the-cloud” paradigm. Naturally, agent-coordination systems are affected by this data-increase phenomenon as they are often used as the basis for pervasive-computing frameworks and cloud-computing systems. There have been a few works on coordination system to include data self-organization (e.g. Swarm Linda) however they generally organize their data based on naive approaches where items are either completely similar or dissimilar (1|0 approach for matching of data). Although this approach is useful, in general-purpose systems where the diversity of data items is large, data items will rarely be considered as plainly similar, leading to a situation where data does not self-organize well. In this paper we move towards a general-purpose approach to organization based on an ontology-defined concept relationship in WordNet. In our approach, data items are seen as concepts that have relation to other concepts: tuples are driven towards one-another at rates that are proportional to the strength of tuple relationship. We demonstrate that this approach leads to a good mechanism to self-organize data in data-intensive environments.
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基于wordnet本体的协调系统自组织
在当今的数据密集型世界中,对数据组织的需求急剧增加。分布式系统正在处理大量的数据,这些数据主要来自普适性计算应用程序的普及和所谓的“云中的数据”范式。当然,代理协调系统会受到这种数据增长现象的影响,因为它们经常被用作普及计算框架和云计算系统的基础。已经有一些关于协调系统的工作,包括数据自组织(例如Swarm Linda),但是他们通常基于幼稚的方法来组织数据,其中项目要么完全相似,要么完全不同(1|0方法来匹配数据)。尽管这种方法很有用,但在数据项多样性很大的通用系统中,数据项很少被认为是完全相似的,从而导致数据不能很好地自组织。在本文中,我们在WordNet中采用了一种基于本体定义的概念关系的通用组织方法。在我们的方法中,数据项被视为与其他概念有关系的概念:元组以与元组关系强度成比例的速度相互驱动。我们证明了这种方法可以在数据密集型环境中产生一种自组织数据的良好机制。
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