• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2606-2626
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• 2016

This article investigates the distributed data storage problem in the space information network (SIN) using distributed fountain codes. Since space nodes in the SIN are resource-limited, in order to reduce energy consumption while improving the storage reliability, an efficient distributed storage based on fountain codes and probabilistic broadcasting (DSFPB) strategy is proposed. In the proposed strategy, source packets are disseminated among the entire network according to probabilistic broadcasting (PBcast), and the final degree distribution is close to the desired robust soliton distribution (RSD), this is benefited from the appropriate packets encoding procedure of the proposed strategy. As presented by the analysis and simulations, the total cost of data dissemination is greatly reduced compared with existing representative strategies, while improving the decoding performance.

• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.285-294
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• 1999

This paper presents a content-search system built on distributed environments using the open product model of STEP, The content-search system searches design data for given product descriptions such as part name and features. Distribute object interfaces has been defined by IDL and distributed product data are searched through CORBA protocols. Web interfaces are also provided for interactive user interfaces. Given a user request, a mediator interacts with distributed search servers and sends collected results back to the user. The mediator has such metadata as location, program name, and other information about product data stored on distributed system. The search servers use SDAI interfaces to search STEP files or databases. The content-search system promotes the reuse of previous design within a company and the outsourcing of part designs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3533-3549
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• 2019

A big database utilizes the establishing network technology, and it became an emerging trend in the computing field. Therefore, there is a necessity for an optimal and effective data distribution approach to deal with this trend. This research presents the practical perspective of designing and implementing distributed database features. The proposed system has been establishing the satisfying, reliable, scalable, and standardized use of information. Furthermore, the proposed scheme reduces the vast and recurring efforts for designing an individual system for each university, as well as it is effectively participating in solving the course equivalence problem. The empirical finding in this study shows the superiority of the distributed system performance based on the average response time and the average waiting time than the centralized system. The system throughput also overcomes the centralized system because of data distribution and replication. Therefore, the analyzed data shows that the centralized system thrashes when the workload exceeds 60%, while the distributed system becomes thrashes after 81% workload.

• Journal of the Korea Society for Simulation
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• v.18 no.1
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• pp.35-40
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• 2009

The reliability of processing the distributed application becomes more and more important issues in distributed network as the usage of distributed network increases. Because the distributed network applications are processed in the available resources of Internet. It is important factors that the user can efficiently access the available resources and processed results can be delivered to the user of job request. Therefore in this paper, we suggested the survivability factor for sending data safely whether it can be efficiently accessed between the user and available resource which processes the distributed application. And evaluated the performance of the suggested factor using the data transmission time. Also we suggested the transmission algorithm for safe transmission using the survivability factor.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.31-40
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• 2005

In this paper, we propose XMDR(XML Metadata Registry) to guarantee the interoperability of data in distributed database, and describe a data synchronizing agent system using it. The proposal of XMDR is to solve the data heterogeneity problem in the sharing and exchanging data. Data heterogeneity problem is generated by different definition or mismatching expression of the same information. Therefore, we define XMDR with XML document by analyzing data elements based on MDR specification. The proposed synchronizing agent system using XMDR not only solves data heterogeneity for data interoperability in synchronizing data but also provides more efficient the agent system by offering errors of low frequency in the number of systems and requests of synchronizing data.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.261-269
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• 2023

We propose to design a Holochain-based security and privacy protection system for resource-constrained IoT healthcare systems. Through analysis and performance evaluation, the proposed system confirmed that these characteristics operate effectively in the IoT healthcare environment. The system proposed in this paper consists of four main layers aimed at secure collection, transmission, storage, and processing of important medical data in IoT healthcare environments. The first PERCEPTION layer consists of various IoT devices, such as wearable devices, sensors, and other medical devices. These devices collect patient health data and pass it on to the network layer. The second network connectivity layer assigns an IP address to the collected data and ensures that the data is transmitted reliably over the network. Transmission takes place via standardized protocols, which ensures data reliability and availability. The third distributed cloud layer is a distributed data storage based on Holochain that stores important medical information collected from resource-limited IoT devices. This layer manages data integrity and access control, and allows users to share data securely. Finally, the fourth application layer provides useful information and services to end users, patients and healthcare professionals. The structuring and presentation of data and interaction between applications are managed at this layer. This structure aims to provide security, privacy, and resource efficiency suitable for IoT healthcare systems, in contrast to traditional centralized or blockchain-based systems. We design and propose a Holochain-based security and privacy protection system through a better IoT healthcare system.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1785-1792
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• 2017

Generally, big data contains sensitive information about individuals, and thus directly releasing it for public use may violate existing privacy requirements. Therefore, privacy-preserving data publishing (PPDP) has been actively researched to share big data containing personal information for public use, while protecting the privacy of individuals with minimal data modification. Recently, with increasing demand for big data sharing in various area, there is also a growing interest in the development of software which supports a privacy-preserving data publishing. Thus, in this paper, we develops the system which aims to effectively and efficiently support privacy-preserving data publishing. In particular, the system developed in this paper enables data owners to select the appropriate anonymization level by providing them the information loss matrix. Furthermore, the developed system is able to achieve a high performance in data anonymization by using distributed Hadoop clusters.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.873-880
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• 2008

This paper deals with the peer-to-peer data communication to connect each distributed levels of developed unmanned system according to the JAUS. The JAUS is to support the acquisition of unmanned system by providing a mechanism for reducing system life-cycle costs. Each of distributed levels of the JAUS protocol divides into a system, some of subsystems, nodes and components/instances, each of which may be independent or interdependence. We have to distribute each of the levels because high performance is supported in order to create several sub-processor computing data in one processor with high CPU speed performance. To complement such disadvantage, we must think the concept that a distributed processing agrees with separating each of levels from the JAUS protocol. Therefore, each of distributed independent levels send data to another level and then it has to be able to process the received data in other levels. So, peer-to-peer communication has to control a data flow of distributed levels. In this research, we explain each of levels of the JAUS and peer-to-peer communication structure among the levels using our developed unmanned ground vehicle.

• The Journal of Society for e-Business Studies
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• v.2 no.2
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• pp.155-169
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• 1997

The CALS integrated database is a key information technology in which CALS implements an information sharing system to enable digital data transfers for technical and non-technical information in distributed and heterogeneous environments. Such heterogeneously distributed CALS information needs to be systematically incorporated so that it can provide a global data view for CALS users. In this paper, we investigated the technologies of CALS integrated database, and proposed a system prototype to implement an integrated data environment (IDE) utilizing distributed object environments CORBA (Common Object Request Broker Architecture).

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