• Title/Summary/Keyword: DBaaS (DataBase as a Service)

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A Design of the Cloud Aggregator on the MapReduce in the Multi Cloud

  • Hwang, Chigon;Shin, Hyoyoung;Lee, Jong-Yong;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.1
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    • pp.83-90
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    • 2016
  • The emergence of cloud has been able to provide a variety of IT service to the user. As organizations and companies are increased that provide these cloud service, many problems arises on integration. However, with the advent of latest technologies such as big data, document-oriented database, and MapReduce, this problem can be easily solved. This paper is intended to design the Cloud Aggregator to provide them as a service to collect information of the cloud system providing each service. To do this, we use the DBaaS(DataBase as a Service) and MapReduce techniques. This makes it possible to maintain the functionality of existing system and correct the problem that may occur depending on the combination.

The Design of Dynamic Fog Cloud System using mDBaaS

  • Hwang, Chigon;Shin, Hyoyoung;Lee, Jong-Yong;Jung, Kyedong
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.4
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    • pp.59-66
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    • 2017
  • Cloud computing has evolved into a core computing infrastructure for the internet that encompasses content, as well as communications, applications and commerce. By providing powerful computing and communications capabilities in the palm of the hand everywhere with a variety of smart devices, mobile applications such as virtual reality, sensing and navigation have emerged and radically changed the patterns people live. The data that is generated is getting bigger. Cloud computing, on the other hand, has problems with system load and speed due to the collection, processing and control of remote data. To solve this problem, fog computing has been proposed in which data is collected and processed at an edge. In this paper, we propose a system that dynamically selects a fog server that acts as a cloud in the edge. It serves as a mediator in the cloud, and provides information on the services and systems belonging to the cloud to the mobile device so that the mobile device can act as a fog. When the role of the fog system is complete, we provide it to the cloud to virtualize the fog. The heterogeneous problem of data of mobile nodes can be solved by using mDBaaS (Mobile DataBase as a Service) and we propose a system design method for this.

Design of Integrated Medical Information System Based on The Cloud

  • Lee, Kwang-Cheol;Moon, Seok-Jae;Lee, Jong-Yong;Jung, KyeDong
    • International journal of advanced smart convergence
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    • v.4 no.1
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    • pp.88-92
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    • 2015
  • Today, the medical information system has evolved in the way of integrated healthcare IT information systems. Therefore, it is trying to build advanced U-Healthcare service. Though the U-Healthcare environments is exchanged the information between systems in many cases, however since the each system is different, the integration and exchange of data is difficult. To overcome this problem, in this paper it proposes that we suggests a possible DBaaS(DataBase as a Service) for the heterogeneous integration of medical information management and data exchange. First, the proposed system builds DBaaS cloud by integrating the meta-DB Schema level and DB Schema for each hospital. And, the mapping the schema data and the existing hospital information system is possible using the International Standard HL7. By applying the proposed method to the hospital system, it comes true the efficient exchange of information between the patients, doctors, staffs through the data mapping of the one to multi-system.

The Design of mBodyCloud System for Sensor Information Monitoring in the Mobile Cloud Environment

  • Park, Sungbin;Moon, Seok-Jae;Lee, Jong-Yong;Jung, Kye-Dong
    • International journal of advanced smart convergence
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    • v.5 no.1
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    • pp.1-7
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    • 2016
  • Recently, introduced a cloud computing technology to the IT industry, smart phones, it has become possible connection between mobility terminal such as a tablet PC. For dissemination and popularization of movable wireless terminal, the same operation have focused on a viable mobile cloud in various terminal. Also, it evolved Wireless Sensor Network(WSN) technology, utilizing a Body Sensor Network(BSN), which research is underway to build large Ubiquitous Sensor Network(USN). BSN is based on large-scale sensor networks, it integrates the state information of the patient's body, it has been the need to build a managed system. Also, by transferring the acquired sensor information to HIS(Hospital Information System), there is a need to frequently monitor the condition of the patient. Therefore, In this paper, possible sensor information exchange between terminals in a mobile cloud environment, by integrating the data obtained by the body sensor HIS and interoperable data DBaaS (DataBase as a Service) it will provide a base of mBodyCloud System. Therefore, to provide an integrated protocol to include the sensor data to a standard HL7(Health Level7) medical information data.

Design of Falling Recognition Application System using Deep Learning

  • Kwon, TaeWoo;Lee, Jong-Yong;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.120-126
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    • 2020
  • Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.