• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.19-27
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• 2010

Historical archived traffic data management system enables a long term time-series analysis and provides data necessary to acquire the constantly changing traffic conditions and to evaluate and analyze various traffic related strategies and policies. Such features are provided by maintaining highly reliable traffic data through scientific and systematic management. Now, the management systems for massive traffic data have a several problems such as, the storing and management methods of a large volume of archive data. In this paper, we describe how to storing and management for the massive traffic data and, we propose methodology for logical and physical architecture, collecting and storing, database design and implementation, process design of massive traffic data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.436-439
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• 2011

As mobile digital devices have come into more widespread use, the demand for mobile storage devices have been increasing rapidly and most of digital cameras and camcorders are using SD memory cards. The SD memory card are generally employing a form of copying data into a personal computer after storing user data based on flash memory. The current paper proposes the SD memory card of being capable of storing photograph and image data through network rather than using a method of storing data in flash memory. By delivering data and memory address values obtained through SD Slave IP to network server without sending them to flash memory, one can store data necessary to be stored in a computer's SD memory in real time in a safe and convenient way.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.744-747
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• 2017

The Internet of things (IoT) needs to be an event-driven approach for efficient real time response and processing. An IoT gateway is sometimes employed to provide the connection and translation between devices and the cloud. Storing data in the local database, and then forwarding it on the cloud is a task to be relegated to a gateway device In this paper, we propose the design of the IoT gateway with Fog computing for storing data from sensors into a local database. In the procedure of designing storing tasks, we propose to use the interfacing software known as Ardulink MQTT bridge. MQTT is a protocol for sensors to publish data to the clients. When it comes to needing historical data, MQTT connector can push MQTT data into SQL database. We write an MQTT client and based on the message topic insert the values into a SQL Database The design of IoT gateway with Fog computing adds value because it provides processing of the data across multiple devices before it sends to the cloud.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.231-234
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• 2020

In the past few years, the industrial internet of things (IIoT) has received great attention in various industrial sectors which have potentially increased a high level of integrity, availability, and scalability. The increasing of IIoT is expected to create new smart industrial enterprises and build the next generation smart system. However existing IIoT systems rely on centralized servers that are vulnerable to a single point of failure and malicious attack, which exposes the data to security risks and storage. To address the above issues, blockchain is widely considered as a promising solution, which can build a secure and efficient environment for data storing, processing and sharing in IIoT. In this paper, we propose a decentralized, peer-to-peer platform for secure data storing in industrial IoT base on the ethereum blockchain. We exploit ethereum to ensure data security and reliability when smart devices store the data.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.697-701
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• 2010

The numbers of digital video cameras are fast increased. Accordingly, digital video data management is becoming more important. Efficient storing method and fast browsing method still remains to be one of significant issue. In this paper, an optimized data storing process without losing information and an organized appearance features indexing method are proposed. Also, the data removing policy could be used to reduce large amount of space and it facilitates fast sequential search. The appearance features index constructs key information of moving objects to answer queries about what people are doing, particularly when, where and who they move. The evaluation results showed better performance in the transfer time and the saving in storage space.

• The Journal of Society for e-Business Studies
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• v.14 no.1
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• pp.57-79
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• 2009

As the Web-based e-Business prevails, the volume of XML data on the Web is getting larger than ever. Although much research has been done on decomposing and storing XML data in RDB, which is now the most popular storage for XML, and on processing XML queries through their SQL counterparts, little attention was paid to how to alleviate the burden of storing massive volume of XML data. In this paper, we propose a hybrid method of storing XML data in RDB, whereby the unit of storage could be an XML subtree as well as an XML node. The part of XML data whose nodes were separately stored could be reformed into an XML subtree for storing when it gets rarely queried or less valuable for reference as time goes by. With this method, we designed and implemented a hybrid XML storage and query processing system, comparing it with the conventional system where an XML node is the only unit of storage. Through experiments, we compared storage efficiency and query processing performance, validating the effectiveness of our proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2588-2609
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• 2019

Speech homomorphic encryption has become one of the key components in secure speech storing in the public cloud computing. The major problem of speech homomorphic encryption is the huge data expansion of speech cipher-text. To address the issue, this paper presents a speech homomorphic encryption scheme with less data expansion, which is a probabilistic statistics and addition homomorphic cryptosystem. In the proposed scheme, the original digital speech with some random numbers selected is firstly grouped to form a series of speech matrix. Then, a proposed matrix encryption method is employed to encrypt that speech matrix. After that, mutual information in sample speech cipher-texts is reduced to limit the data expansion. Performance analysis and experimental results show that the proposed scheme is addition homomorphic, and it not only resists statistical analysis attacks but also eliminates some signal characteristics of original speech. In addition, comparing with Paillier homomorphic cryptosystem, the proposed scheme has less data expansion and lower computational complexity. Furthermore, the time consumption of the proposed scheme is almost the same on the smartphone and the PC. Thus, the proposed scheme is extremely suitable for secure speech storing in public cloud computing.

• International Journal of Internet, Broadcasting and Communication
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• v.5 no.1
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• pp.14-17
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• 2013

RDF data is widely used for exchanging data nowadays to enable semantic web era. This leads to the need for storing and retrieving these data efficiently and effectively. Recently, the structure index in graph-based perspective is considered as a promising approach to deal with issues of complex query graphs. However, even though there are many researches based on structure indexing, there can be a better architectural approach instead of addressing the issue as a part. In this research, we propose architecture for storing, query processing and retrieving RDF data in efficient manner using structure indexing. Our research utilizes research results from iStore and 2 relation-based approaches and we focus on improving query processing to reduce the time of loading data and I/O cost.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.45-48
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• 2013

In this paper, we proposed an Indexing Structure System (ISS) based on Apache Hadoop in Wireless Sensor Network (WSN). Nowadays sensors data continuously keep growing that need to control. Data constantly update in order to provide the newest information to users. While data keep growing, data retrieving and storing are face some challenges. So by using the ISS, we can maximize processing quality and minimize data retrieving time. In order to design ISS, Indexing Types have to be defined depend on each sensor type. After identifying, each sensor goes through the Indexing Structure Processing (ISP) in order to be indexed. After ISP, indexed data are streaming and storing in Hadoop Distributed File System (HDFS) across a number of separate machines. Indexed data are split and run by MapReduce tasks. Data are sorted and grouped depend on sensor data object categories. Thus, while users send the requests, all the queries will be filter from sensor data object and managing the task by MapReduce processing framework.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.3
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• pp.157-162
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• 2012

In this paper, we propose a flight data storing system for effective data processing. Since the flight data contains critical information and their sizes are vast, encryption and compression would be needed to manage the flight data in effect. And we implemented the flight data storing system using an embedded board with DSP based on DPCM compression and AES encryption. Especially, we applied the reordering technique to advance the security function. From the simulations for two type data of voice and avionics, we found the developed system is well performed.