本体驱动的语义物联网云服务协同方法研究

发布时间：2018-05-12 14:56

本文选题：本体 + 语义物联网　；参考：《大连海事大学》2017年硕士论文

【摘要】：语义物联网环境下的前端传感器设备具有感知和标识能力,其数据特点是庞杂繁多且较为分散,受限于前端感知设备储存和处理数据的能力,需要依赖云计算技术强劲的运算能力以降低终端设备本身的复杂性。而目前而言,不同的云服务提供商在服务描述、服务规格等方面并没有统一的标准,并且存在着大量功能相似的冗余现象,在云服务数量不断增加的情况下,传统的基于关键字搜索很难从海量异构云服务中准确而高效地发现合适的服务信息,云服务协同问题日益突出。为了解决标准的缺失导致目前云服务协同水平难以满足用户需求这一问题,本文提出了一种本体驱动的语义物联网云服务协同方法。本论文基于OWL本体来实现语义物联网环境下云服务协同,参照国外研究机构对于语义协同、互操作、云服务语义表示等相关领域的研究成果,提出语义物联网环境下本体驱动的云服务协同框架。首先,通过基于REVERB的信息抽取和基于WordNet的概念扩展,对云服务描述信息和需求信息分别进行预处理,并得到特定格式的描述文件;接着,针对预处理后的云服务描述信息进行语义标注,并将TF-JDF权重与本体语义距离相结合构建云服务的语义索引,经过匹配模块处理后获取到符合用户指定功能要求的云服务信息;然后,通过参考语义物联网云服务的服务质量参数并充分考虑到用户需求的不确定性,定义了云服务QoS属性信息五元组表示形式,并采用基于模糊QoS的云服务选择算法,将服务请求结果按计算出的综合满意程度排序并反馈给用户。为了验证上述方法在语义物联网环境下的有效性,本论文最终设计并实现了本体驱动的语义物联网云服务协同原型系统。该系统从功能上分为信息预处理模块、云服务语义匹配模块、云服务目录管理模块以及云服务选择模块,分别实现了云服务信息的预处理、构建基于本体的云服务目录、云服务语义匹配及基于模糊QoS的云服务选择功能。通过实验数据对该系统的查准率和召回率进行综合考量,实验结果表明该方法可以针对用户需求提供更加合适的云服务信息供用户选择。
[Abstract]:The front-end sensor devices in the semantic Internet of things environment have the ability of perception and identification, and their data is characterized by a large variety and relatively scattered, limited by the front-end sensing devices' ability to store and process data. Rely on the strong computing power of cloud computing technology to reduce the complexity of the terminal device itself. However, at present, different cloud service providers do not have uniform standards in service description, service specification and other aspects, and there are a large number of similar redundancy phenomena, in the case of increasing number of cloud services, Traditional keyword-based search is difficult to find the appropriate service information accurately and efficiently from massive heterogeneous cloud services, and the problem of cloud service collaboration is becoming more and more prominent. In order to solve the problem that the level of cloud service collaboration is difficult to meet the needs of users due to the lack of standards, this paper proposes an ontology-driven method for cloud service collaboration in the semantic Internet of things. This thesis is based on OWL ontology to realize cloud service collaboration in the environment of semantic Internet of things, referring to the research results of foreign research institutions on semantic collaboration, interoperability, semantic representation of cloud services, and so on. An ontology driven cloud service collaboration framework is proposed in the semantic Internet of things environment. Firstly, through the information extraction based on REVERB and the concept extension based on WordNet, the description information and requirement information of cloud services are preprocessed, and a description file with specific format is obtained. The semantic index of cloud service is constructed by combining TF-JDF weight with semantic distance of ontology. After processing by matching module, the information of cloud service can be obtained according to the requirement of user specified function. Then, by referring to the QoS parameters of the semantic Internet of things cloud services and taking full account of the uncertainty of user requirements, the five-tuple representation of cloud service QoS attribute information is defined, and the cloud service selection algorithm based on fuzzy QoS is adopted. The service request results are sorted according to the calculated overall satisfaction and fed back to the user. In order to verify the effectiveness of the above methods in the semantic Internet of things environment, this paper finally designed and implemented the ontology driven semantic Internet of things cloud service collaborative prototype system. The system is divided into information preprocessing module, cloud service semantic matching module, cloud service directory management module and cloud service selection module. Cloud service semantic matching and cloud service selection based on fuzzy QoS. The experimental results show that the proposed method can provide more appropriate cloud service information for users to choose from.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.44;TN929.5;TP393.09

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