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- Cai, Hongming, et al.
(författare)
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IoT-Based Big Data Storage Systems in Cloud Computing : Perspectives and Challenges
- 2017
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Ingår i: IEEE Internet of Things Journal. - : IEEE. - 2327-4662. ; 4:1, s. 75-87
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Tidskriftsartikel (refereegranskat)abstract
- Internet of Things (IoT) related applications have emerged as an important field for both engineers and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations especially in cloud computing. This paper first provides a functional framework that identifies the acquisition, management, processing and mining areas of IoT big data, and several associated technical modules are defined and described in terms of their key characteristics and capabilities. Then current research in IoT application is analyzed, moreover, the challenges and opportunities associated with IoT big data research are identified. We also report a study of critical IoT application publications and research topics based on related academic and industry publications. Finally, some open issues and some typical examples are given under the proposed IoT-related research framework
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- Cai, Hongming, et al.
(författare)
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Web of Things Data Storage
- 2017
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Ingår i: Managing the Web of Things. - : Elsevier. - 9780128097656 - 9780128097649 ; , s. 325-354
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Bokkapitel (refereegranskat)abstract
- With the wide spread of Web of Things (WoT) technology, massive data are generated by huge amounts of distributed sensors and different applications. WoT related applications have emerged as an important area for both engineers and researchers. As a consequence, how to acquire, integrate, store, process and use these data has become an urgent and important problem for enterprises to achieve their business goals. Based on data processing functional analysis, a framework is provided to identify the representation, management, and disposing areas of WoT data. Several associated functional modules are defined and described in terms of their key characteristics and capabilities. Then, current researches in WoT applications are organized and compared to show the state-of-the-art achievements in literature from the view of data processing process. Next, some WoT storage techniques are discussed to enable WoT applications to move into cloud platforms. Lastly, based on application requirement analysis, some future technical tendencies are also proposed.
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- Mao, Junjie, et al.
(författare)
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A Web of Things Based Device-adaptive Service Composition Framework
- 2016
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Ingår i: 2016 IEEE 13th International Conference on e-Business Engineering (ICEBE). - : IEEE. - 9781509061198 - 9781509061204 ; , s. 40-47
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Konferensbidrag (refereegranskat)abstract
- In WoT environment, smart things provide RESTful services to expose their resources and operations. There are a large number of smart things that offer the same functionalities but have different service interfaces. Because of the high coupling between device service instances and process specifications like BPEL, the cost of reusing a BPEL specification between different device environments could be extremely high. We propose a device-adaptive service composition framework for WoT environment, in order to help users to apply the business process and service composition technologies more conveniently. In the framework, we design an activity description model, which is a semantic description for business activities, to overcome the shortcoming of directly binding the process and the service. Then, a matching mechanism between the model and the WADL of device services is proposed to select candidate services for the composition. Furthermore, we represent the matching result in a logical composition model, with which the source code of a general service can be automatically generated. The general service is a unified encapsulation for device services that match the functionalities of business activity. So user can interact with the general service instead of the origin services on the device, which decouples the process specification and the actual device services. A case study is offered to illustrate how to apply our framework in an intelligent charging pile sharing platform.
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