[论文解读] Data Mining definition services in Cloud Computing with Linked Data.

Manuel Parra-Royón, Ghislain Auguste Atemezing+1 more|arXiv (Cornell University)|Jun 18, 2018

Service-Oriented Architecture and Web Services被引用 2

一句话总结

本文提出了一种基于链接数据的模式，用于在云计算中定义数据挖掘服务，通过重用现有的语义模式，实现跨服务提供商的互操作性和可移植性。该方法对定价、接口、服务等级协议（SLAs）和工作流程等关键服务方面进行建模，并通过真实服务定义和一个全面的云服务提供商数据集进行了验证。

ABSTRACT

In recent years with the rise of Cloud Computing, many companies providing services in the cloud, are empowering a new series of services to their catalogue, such as data mining and data processing, taking advantage of the vast computing resources available to them. Different service definition proposals have been put forward to address the problem of describing services in Cloud Computing in a comprehensive way. Bearing in mind that each provider has its own definition of the logic of its services, and specifically of data mining services, it should be pointed out that the possibility of describing services in a flexible way between providers is fundamental in order to maintain the usability and portability of this type of Cloud Computing services. The use of semantic technologies based on the proposal offered by Linked Data for the definition of services, allows the design and modelling of data mining services, achieving a high degree of interoperability. In this article a schema for the definition of data mining services on cloud computing is presented considering all key aspects of service, such as prices, interfaces, Software Level Agreement, instances or data mining workflow, among others. The new schema is based on Linked Data, and it reuses other schemata obtaining a better and more complete definition of the services. In order to validate the completeness of the scheme, a series of data mining services have been created where a set of algorithms such as Random Forest or K-Means are modeled as services. In addition, a dataset has been generated including the definition of the services of several actual Cloud Computing data mining providers, confirming the effectiveness of the schema.

研究动机与目标

• 解决云计算中数据挖掘服务缺乏标准化、可互操作的服务描述问题。
• 实现跨异构云服务提供商的灵活且可移植的数据挖掘服务定义。
• 利用链接数据原则和可重用模式，实现更完整且语义丰富的服务建模方法。
• 通过真实云服务提供商服务和代表性数据集，验证该模式的完整性和有效性。

提出的方法

• 基于链接数据原则和现有本体，设计数据挖掘服务的语义模式。
• 整合核心服务方面，包括定价、接口、服务等级协议（SLAs）以及数据挖掘工作流程。
• 将随机森林和K-均值等特定算法作为一等公民的云服务，纳入该模式中。
• 重用并互操作于已建立的语义模式，以增强表达力和一致性。
• 使用真实云服务提供商服务的数据集（包括服务定义和元数据）实现并验证该模式。

实验结果

研究问题

• RQ1 如何描述云计算中的数据挖掘服务，以确保在不同服务提供商之间的互操作性和可移植性？
• RQ2 链接数据和语义模式在多大程度上能提升服务描述的完整性和可重用性？
• RQ3 统一的模式能否以一致且可扩展的方式对定价、SLA和工作流程等关键服务方面进行建模？
• RQ4 该提出的模式在多大程度上能有效表示现有云服务提供商的真实数据挖掘服务？

主要发现

• 所提出的模式成功使用语义网标准对数据挖掘服务的关键组件（包括接口、定价、SLA和工作流定义）进行了建模。
• 通过重用现有模式，该方法在服务描述中实现了更高的表达力和一致性。
• 该模式通过提供统一的、机器可处理的服务定义格式，实现了云服务提供商之间的互操作性。
• 使用真实云服务提供商服务数据集的验证结果证实了该模式的完整性和实际适用性。