• 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.

• Journal of The Korean Association of Information Education
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• v.18 no.3
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• pp.381-390
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• 2014

It is a general tendency that a traditional class management system is operated by teachers' arbitrary decision. However, at the present day, it is needed that both students and teachers make an autonomy standard manual and manage the class by themselves in order to cultivate the qualified democratic citizen. Therefore existing class management systems do not meet present classes with diversity. In this paper, we design a new web application framework using REDIS(Remote Dictionary System) for class management. REDIS is a kind of data repository to store various key values and also generally provides a solution of developing web applications with shared memories. We designed a web application framework to maximize both convenience of use and accessibility. The scalability of the class management system can be effectively enhanced using diverse template functions which are basically provided by the framework.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.476-479
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• 2021

DBMS 파라미터 튜닝이란 데이터베이스에서 제공하는 다양한 파라미터의 값을 조율하여, 최적의 성능을 도출하는 과정이다. 데이터베이스 종류에 따라 파라미터 개수가 수십 개에서 수백 개로 다양하며, 각 기능이 모두 다르기 때문에 최적의 조합을 찾는 것은 쉽지 않다. 선행 연구에서는 BO 기법을 사용하여 적절한 파라미터 값을 추출했지만, 파라미터 개수에 비례하여 차원이 커지는 문제가 발생한다. 본 논문에서는 통계적으로 파라미터를 분류하여 탐색 공간을 줄인 다음 단계적으로 BO 를 수행하는 PBO 방식을 제안한다. 파라미터 값을 랜덤하게 할당하여 벤치마킹한 결과값을 군집화한 후, 각 군집별로 파라미터와의 연관성을 분석해 높은 상관관계를 가진 파라미터를 매칭시켜 분류한다. 제안하는 방법론을 검증하기 위하여 8 가지 회귀 모델과의 비교 실험을 통해 제안한 방법론의 우수성을 검증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2064-2072
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• 2015

To improve performance, most of Web Services produce and manage User Access Logs. Through the Access Logs, the record provides information about time when the most traffic happens and logs and which resource is mostly used. Then, the log can be used to analyze. However, in case of increasing high traffics of Web Services at the specific time, the performance of Web Service leads to deterioration because the number of processing User Access Logs is increasing rapidly. To solve this problem, we should improve the system performance, or tuning is needed, but it makes a problem cost a lot of money. Also, after it happens, it is not necessary to build such system by spending extra money. Therefore, this paper described the effective Web Service's performance as using improved User Access Log performance. Also, to process the newest data in bulk, this paper includes a method applying some parts of NoSQL using Redis.

• ETRI Journal
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• v.42 no.5
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• pp.748-760
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• 2020

MapReduce is a framework that can process huge datasets in parallel and distributed computing environments. However, a single machine failure during the runtime of MapReduce tasks can increase completion time by 50%. MapReduce handles task failures by restarting the failed task and re-computing all input data from scratch, regardless of how much data had already been processed. To solve this issue, we need the computed key-value pairs to persist in a storage system to avoid re-computing them during the restarting process. In this paper, the task failure resilience (TFR) technique is proposed, which allows the execution of a failed task to continue from the point it was interrupted without having to redo all the work. Amazon ElastiCache for Redis is used as a non-volatile cache for the key-value pairs. We measured the performance of TFR by running different Hadoop benchmarking suites. TFR was implemented using the Hadoop software framework, and the experimental results showed significant performance improvements when compared with the performance of the default Hadoop implementation.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.293-298
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• 2017

Recently, much research has been devoted to implementing and provisioning high-performance computing environment using clusters with multiple computers and high-performance networking technologies. In-memory based Key-Value stores, such as Redis or Memcached, are widely used in high performance cluster environments to improve the data processing performance. We can distribute data at different storage nodes, and each computing node can access it at a high speed using these In-memory based Key-Value stores. InfiniBand is a de-facto technology that is widely used to interconnect each node of a cluster. In this paper, we propose a new data pre-fetching scheme for Key-Value store based on high performance clusters to improve the performance. The proposed scheme utilizes the data transfer characteristics of InfiniBand. The results of the simulation show that the proposed scheme can reduce the data transfer time by up to about 28%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.298-305
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• 2016

Various NoSQL databases are more excellent to process a large amount of big data than existing relational databases such as MySQL, PostgreSQL and Oracle. Among widely used NoSQL databases, performance of HBase, Cassandra, MongoDB and Redis was comparatively assessed. For distributed processing of a large amount of data, 12 servers were connected through switching hub and Ubuntu was installed as operating system. As for benchmark tool, YCSB was applied. Read and update ratios changed from 50% and 50%, 95% and 5% and finally, 100% and 0% and each of them was assessed as 200,000 commands developed into 1,200,000 commands for each case. Cassandra was most excellent with transaction processing per second while MongoDB was most excellent with the number of processes carried out per unit time.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.109-121
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• 2020

As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.88.3-89
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• 2017

We present our experiences with open-source NoSQL database systems in analyzing spatial and temporal astronomical data. We conduct experiments of using Redis in-memory NoSQL database system by modifying and exploiting its support of geohash for astronmical spatial data. Our experiment focuses on performance, cost, difficulty, and scalability of the database system. We also test OpenTSDB as a possible NoSQL database system to process astronomical time-series data. Our experiments include ingesting, indexing, and querying millions or billions of astronomical time-series measurements. We choose our KMTNet data and the public VVV (VISTA Variables in the Via Lactea) catalogs as test data. We discuss issues in using these NoSQL database systems in astronomy.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.71.2-71.2
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• 2019

We have developed and tested a prototype system to process transient alert messages from the currently working facilities such as Gaia and GCN notices. Our experiments with the prototype focus on developing a platform that can be used in the LSST era with about 10 million alerts per night and helping Korean community members with the automated processing environment to provide auxiliary information for every alert message. The system consists of a message broker implemented by Redis and multiple message subscribers specialized for specific scientific interests. The current implementation of the entire system allows new Korean members to adopt their own processing chains receiving the messages from our local broker. We welcome experimental ideas and opinions from the Korean community about the current message processing system. We plan to test the current system with the ZTF alerts in the near future.