• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.911-917
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• 2023

In today's world, we find ourselves facing energy crises due to factors such as war and climate crises. To prepare for these energy crises, many researchers continue to study systems related to energy monitoring and conservation, such as energy management systems, energy monitoring, and energy conservation. In line with these efforts, nations are making it mandatory for energy-consuming facilities to implement these systems. However, these facilities, limited by space and energy constraints, are exploring ways to improve. This research explores the operation of a data collection system using low-performance embedded devices. In this context, it proves that an optimized version of RocksDB, a Key-Value store, outperforms traditional databases when it comes to time-series data. Furthermore, a comprehensive database evaluation tool was employed to assess various databases, including optimized RocksDB and regular RocksDB. In addition, heterogeneous databases and evaluations are conducted using a UD Benchmark tool to evaluate them. As a result, we were able to see that on devices with low performance, the time required was up to 11 times shorter than that of other databases.

• The Journal of Information Systems
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• v.19 no.3
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• pp.181-208
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• 2010

As knowledge-based society comes to the fore, sharing knowledge becomes a hot issue. Among various types of knowledge, a significance of software(applications) and contents is a huge in a current society. Moreover, along with appearance of smartphone, for instance iPhone, Application Store(also known as AppStore) utilized as a common gateway for sharing software and contents, brings a big interest for many users and developers. However, prior research to understand users' behavior on AppStore has been a scant. Therefore, the main purpose of this study is to investigate the impact of key smart service environmental factors on AppStore in order to empirically explain users' psychological feelings of intention to use AppStore. Based on a well-known technology adoption model, TAM, the study incorporates three main characteristics(user, society, and service) with six constructs(Innovation, Enjoyment, Subjective Norm, Information Level, Content variety, and Cost), influencing perceived usefulness, which then affects users' intention to use AppStore. Results provide evidence that support the tested hypotheses. The implications of the findings suggest a new theoretical work for future AppStore research and offers suggestions that the researchers and practitioners of AppStore should consider regarding the development of application and contents.

• Korea Information Processing Society Review
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• v.23 no.4
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• pp.19-26
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• 2016

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.107-112
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• 2020

Recently, unstructured data is rapidly being produced based on web-based services. NoSQL systems and key value stores that process unstructured data as key and value pairs are widely used in various applications. In this paper, a study was conducted on a skip list used for in-memory data management in an LSM-tree based key value store. The skip list used in the key value store is an insertion-based skip list that does not allow overwriting and processes all changes only by inserting. This behavior can support Multi-Version Concurrency Control (MVCC), which can simultaneously process multiple read/write requests through snapshot isolation. However, since duplicate keys exist in the skip list, the performance significantly degrades due to unnecessary node visits during a list traverse. In particular, serious overhead occurs when a range query or scan operation that collectively searches a specific range of data occurs. This paper proposes a newly designed Stride SkipList to reduce this overhead. The stride skip list additionally maintains an indexing pointer for the last node of the same key to avoid unnecessary node visits. The proposed scheme is implemented using RocksDB's in-memory component, and the performance evaluation shows that the performance of SCAN operation improves by up to 350 times compared to the existing skip list for various workloads.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.102-110
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• 2024

Blockchain records all transactions issued by users, which are then replicated, stored, and shared by participants of the blockchain network. Therefore, the capacity of the ledger stored by participants continues to increase as the blockchain network operates. In order to address this issue, research is being conducted on methods that enhance storage efficiency while ensuring that valid values are stored in the ledger even in the presence of device failures or malicious participants. One direction of research is applying techniques such as Reed-Solomon encoding to the storage of blockchain ledgers. In this paper, we apply Reed-Solomon encoding to the key-value store used for ledger storage in an open-source blockchain, and measure the storage efficiency and increasing computational overhead. Experimental results confirm that storage efficiency increased by 86% while the increase in CPU operations required for encoding was only about 2.7%.

• Journal of Distribution Science
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• v.19 no.7
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• pp.75-85
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• 2021

Purpose: This study is focused on analyzing the key reasons why One-brand Shop has been shrinking and Multi-brand shop is rising from the perspective of the trend changes of customer behavior and distribution channel in the Korean cosmetic market. The purpose of this study is to examine the factors influencing the attractiveness of cosmetics distribution channels from a store perspective and a consumer perspective. Research methodology: This study conducted a survey to define the factors that influence the attractiveness of cosmetics distribution channels. A total of 300 samples were investigated. Results: The store factors that influence the attractiveness of the cosmetics distribution channel were product quality, shopping convenience, and store accessibility in the group of single-brand store preferences, and product diversity and store experience in the group of multi-brand store preferences. Conclusions: Core competing factors of One-brand shop include product value, shopping convenience and accessibility. In contrast, Multi-Brand shops offer core competing factors of diversified product portfolio and shop function experience. A new trend has been found that the customer segments of the price-oriented group and the pleasure-oriented group have become the mainstream segments in the Korean cosmetic market. In conclusion, Multi-brand Shops are suggesting better overall customer experiences in terms of distribution channel attractiveness and customer values.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.111-116
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• 2023

The WiscKey database, which optimizes overhead by compaction of the LSM tree-based Key-Value database, stores the value in a separate file, and stores only the key and value addresses in the database. Each time an fsync system call function is used to ensure data integrity in the process of storing values. In previously conducted studies, workload performance was reduced by up to 5.8 times as a result of performing the workload without calling the fsync system call function. However, it is difficult to ensure the data integrity of the database without using the fsync system call function. In this paper, to reduce the overhead of the fsync system call function while performing workloads on the WiscKey database, we use NVDIMM caching techniques to ensure data integrity while improving the performance of the WiscKey database.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.12
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• pp.1367-1372
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• 2015

In this paper, we embed RFID tag into name plate of pole and store key value at its RFID tag in order to solve the problem for the management of name plate of pole, which identify by eyes of human for until now. The 900MHz RFID reader performs identification for stored key value, then its key value transmit into smart phone through Bluetooth. The smart phone transmit the key value into server through data communication network and receive again the necessary information after the authentication by the server. We develop pole information system that have such a structure.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.5
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• pp.117-126
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• 2016

Recently, increasing utilization of Big Data or Social Network Service involves the increases in demand for NoSQL Database that overcomes the limitations of existing relational database. A forensic examination of Relational Database has steadily researched in terms of Digital Forensics. In contrast, the forensic examination of NoSQL Database is rarely studied. In this paper, We introduce Redis (which is) based on Key-Value Store NoSQL Database, and research the collection and analysis of forensic artifacts then propose recovery method of deleted data. Also we developed a recovery tool, it will be verified our recovery algorithm.