• KIISE Transactions on Computing Practices
• /
• v.22 no.6
• /
• pp.278-283
• /
• 2016

Due to explosive increase in the amount of data produced recently, cloud storage system is required to offer high and stable performance. However, VM (Virtual Machine) migration may result in lowered storage service performance. Especially, in an environment where the host-side flash cache is used in a cloud system, the existing warmed up cache is lost and the problematic cold start begins at a new cache due to a VM migration. In this paper, we first demonstrate and analyze the cold start problem and then propose Cachemior (Cache migrator) which enables efficient hot start of the flash cache.

• Smart Media Journal
• /
• v.4 no.3
• /
• pp.62-67
• /
• 2015

The trend keywords in ICT sector will be Big Data, Internet of Things, and Cloud Computing. The rear end to support those techniques requires a large-capacity storage technology of low-cost. Therefore, we proposed the prototype of low-cost and mass distributed storage system based on PC using open-source Ceph FS for SMB.

• International journal of advanced smart convergence
• /
• v.13 no.3
• /
• pp.135-142
• /
• 2024

Recently, along with digital transformation, technologies such as cloud computing, big data, and artificial intelligence have been actively introduced. In a situation where these technological changes are progressing rapidly, it is often difficult to manage processes efficiently using existing simple workflow management methods. Companies providing current cloud services are adopting virtualization technologies, including virtual machines (VMs) and containers, in their distributed system infrastructure for automated application deployment. Accordingly, this paper proposes a process-based orchestration system for integrated execution of corporate process-oriented workloads by integrating the potential of big data and machine learning technologies. This system consists of four layers as components for performing workload processes. Additionally, a common information model is applied to the data to efficiently integrate and manage the various formats and uses of data generated during the process creation stage. Moreover, a standard metadata protocol is introduced to ensure smooth exchange between data. This proposed system utilizes various types of data storage to store process data, metadata, and analysis models. This enables flexible management and efficient processing of data.

• The Journal of the Korea Contents Association
• /
• v.13 no.8
• /
• pp.28-35
• /
• 2013

Recently, cloud data management has been actively studied along with the development of a cloud computing technology that can process large amounts of data at a lower cost. However, the existing cloud computing platforms do not guarantee interoperability according to the construction environments of users because they do not provide technical and political openness. In other words, in order for users to receive the related services, they use services provided by only one vendor. In this paper, we design and implement a storage interface that supports the international standard CDMI in order to retrieve, update, and delete data in could environments. These interfaces provide the functionality required for developers who want to build and use the cloud storage without special restrictions. In addition, we verify the operability and usability of CDMI international standard through the implementation of the proposed system.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.16 no.2
• /
• pp.35-43
• /
• 2020

Cloud computing integrates computing resources such as servers, storage, and networks with virtualization technology to provide suitable services according to user needs. Due to the structural characteristics of sharing physical resources based on virtualization technology, threats to availability can occur, so it is essential to respond to availability threats in cloud computing. Existing over-provisioning method is not suitable because it can generate idle resources and cause under-provisioning to degrade or disconnect service. System resources must be allocated in real-time according to the system load to guarantee the cloud system's availability. Through appropriate management measures, it is necessary to reduce the system load and increase the performance of the system. This paper analyzes the work response time according to the allocation or migration of virtual machines and discusses an efficient resource management method considering the system load.

• Proceedings of Korean Society of Archives and Records Management
• /
• 2019.05a
• /
• pp.61-67
• /
• 2019

Recently, the central government organizations have changed their Business Management System to the cloud-based On-nara Document 2.0. According to this, the National Archives of Korea is spreading a cloud-based records management system. With the development of digital technology, including cloud computing, preservation and utilization of records must be redesigned continuously to be effective and efficient. It is needed that the process and method of the electronic records management will change from simple digitization of paper-based recording to digital technology. This article offers opinions related to the logical transfer, storage and redundancy elimination of digital objects, machine-readable format, big-data analysis, templates of official documents, and authenticity authentication system based on universally unique identifiers (UUID) and hash value.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.5
• /
• pp.249-258
• /
• 2019

In the cyber-physical system, big data collected from numerous sensors and IoT devices is transferred to the Cloud for processing and analysis. When transferring data to the Cloud, merging data into one single file is more efficient than using the data in the form of split files. However, current merging and splitting operations are performed at the user-level and require many I / O requests to memory and storage devices, which is very inefficient and time-consuming. To solve this problem, this paper proposes kernel-level partitioning and combining operations. At the kernel level, splitting and merging files can be done with very little overhead by modifying the file system metadata. We have designed the proposed algorithm in detail and implemented it in the Linux Ext4 file system. In our experiments with the real Cloud storage system, our technique has achieved a transfer time of up to only 17% compared to the case of transferring split files. It also confirmed that the time required can be reduced by up to 0.5% compared to the existing user-level method.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.2
• /
• pp.119-126
• /
• 2024

The volume of genomic data is constantly increasing in various modern industries and research fields. This growth presents new challenges and opportunities in terms of the quantity and diversity of genetic data. In this paper, we propose a distributed cloud system for integrating and managing large-scale gene databases. By introducing a distributed data storage and processing system based on the Hadoop Distributed File System (HDFS), various formats and sizes of genomic data can be efficiently integrated. Furthermore, by leveraging Spark on YARN, efficient management of distributed cloud computing tasks and optimal resource allocation are achieved. This establishes a foundation for the rapid processing and analysis of large-scale genomic data. Additionally, by utilizing BigQuery ML, machine learning models are developed to support genetic search and prediction, enabling researchers to more effectively utilize data. It is expected that this will contribute to driving innovative advancements in genetic research and applications.

• International Journal of Computer Science & Network Security
• /
• v.23 no.2
• /
• pp.89-95
• /
• 2023

Cloud computing today provides huge computational resources, storage capacity, and many kinds of data services. Data sharing in the cloud is the practice of exchanging files between various users via cloud technology. The main difficulty with file sharing in the public cloud is maintaining privacy and integrity through data encryption. To address this issue, this paper proposes an Enhanced RSA encryption schema (ERSA) for data sharing in the public cloud that protects privacy and strengthens data integrity. The data owners store their files in the cloud after encrypting the data using the ERSA which combines the RSA algorithm, XOR operation, and SHA-512. This approach can preserve the confidentiality and integrity of a file in any cloud system while data owners are authorized with their unique identities for data access. Furthermore, analysis and experimental results are presented to verify the efficiency and security of the proposed schema.

• Journal of the Korea Society for Simulation
• /
• v.24 no.3
• /
• pp.77-87
• /
• 2015

Defense M&S (Modeling & Simulation) is utilized as a realistic method to analyze MOE (Measure of Effectiveness) of weapon systems by modeling weapons and their operational environment on the computer, and simulating them under various war scenarios. As weapon systems become complex in their structure and dynamics, model engineering are experiencing difficulties to construct simulation models on a computer. A model repository helps model developers to save model development time and cost by systematically storing predefined and already validated models. However, most repositories for Defense M&Shave not been successful partly due to limited accessability, vulnerability to security threats, and low level of dependability. In this paper, we propose W-Cloud (Weapon Cloud), a cloud model repository for reusing predefined weapon models. Clients can access W-Cloud on any platforms and various devices, yet security and confidentiality concerns are guaranteed by employing multi-tier information protection mechanism.