• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.678-685
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• 2010

One of the computer application fields which started showing noticeable new growth trends in recent years is the real time communication distributed computing application field. Object-oriented(OO) real time(RT) distributed computing is a form of real-time distributed computing realized with a distributed computer system structured in the form of an object network. In this paper, we describes the application environment as the patient monitor telemedicine system with TMO structure. Vital sign information web viewer systems is also the standard protocol for medical image and transfer. In order to embrace new technologies as telemedicine service, it is important to develope the standard protocol between different systems in the hospital, as well as the communication with external hospital systems. We implemented integration patient monitor telemedicine system between vital sign web viewer systems and hospital information systems.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.32-43
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• 2013

These days, there are more and more IT research institutions which foresee cloud services as the predominant IT service in the near future and there, in fact, are actual cloud services provided by some IT leading vendors. Regardless of physical location of the service and environment of the system, cloud service can provide users with storage services, usage of data and software. On the other hand, cloud service has challenges as well. Even though cloud service has its edge in terms of the extent to which the IT resource can be freely utilized regardless of the confinement of hardware, the availability is another problem to be solved. Hence, this paper is dedicated to tackle the aforementioned issues; prerequisites of cloud computing for distributed file system, open source based Hadoop distributed file system, in-memory database technology and high availability database system. Also the author tries to body out the high availability mass distributed data management architecture in cloud service's perspective using currently used distributed file system in cloud computing market.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.1-9
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• 2016

Algorithms implementing distributed shared memory (DSM) were developed for ensuring consistency. The performance of DSM algorithms is dependent on system and usage parameters. However, ensuring these algorithms to tolerate faults is a problem that needs to be researched. In this study, we proposed fault-tolerant scheme for DSM system and analyzed reliability and fault-tolerant overhead. Using our analysis, we can choose a proper algorithm for DSM on error prone environment.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1153-1156
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• 1987

This paper presents a distributed algorithm for deadlock detection in distributed computing system. The deadlock could be detected optimally from cycle. This algorithm maintains the Process-Resource Table and it could be found the deadlock from the table.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.165-172
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• 2023

Heterogeneous computing is a technology that utilizes different types of processors to perform parallel processing. It maximizes task processing and energy efficiency by leveraging various computing resources such as CPUs, GPUs, and FPGAs. On the other hand, edge computing has developed with IoT and 5G technologies. It is a distributed computing that utilizes computing resources close to clients, thereby offloading the central server. It has evolved to intelligent edge computing combined with artificial intelligence. Intelligent edge computing enables total data processing, such as context awareness, prediction, control, and simple processing for the data collected on the edge. If heterogeneous computing can be successfully applied in the edge, it is expected to maximize job processing efficiency while minimizing dependence on the central server. In this paper, experiments were conducted to verify the feasibility of various parallel programming models on high-end and low-end edge devices by using benchmark applications. We analyzed the performance of five parallel programming models on the Raspberry Pi 4 and Jetson Orin Nano as low-end and high-end devices, respectively. In the experiment, OpenACC showed the best performance on the low-end edge device and OpenSYCL on the high-end device due to the stability and optimization of system libraries.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1171-1185
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• 2014

Rhipe that integrates R and Hadoop environment, made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data and simulated data. Experimental results for comparing the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster, showed fully-distributed mode was more fast than pseudo-distributed mode and computing speeds of fully-distributed mode were faster as the number of data nodes increases. We also compared the performance of our Rhipe with stats and biglm packages available on bigmemory. The results showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.4
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• pp.440-448
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• 1999

본 논문은 객체지향형 분산처리 환경 하에서 오디오나 비디오 등과 같은 실시간(real-time) 스트림(stream) 데이타를 처리하는 데 필요한 소프트웨어 기반구조를 설계하고 구현한 내용을 기술한다. 본 논문에서 제시한 DAViS(Distributed Object Framework supporting Audio/Video Streaming)는, 오디오/비디오 데이타의 처리와 관련된 여러 소프트웨어 구성요소들을 분산객체로 추상화하고, 그 객체들간의 제어정보 교환경로와 오디오/비디오 데이타 전송경로를 서로 분리하여 처리한다. 분산응용프로그램 작성자는 DAViS에서 제공하는 서비스들을 이용하여, 기존의 분산프로그래밍 환경이 제공하는 것과 동일한 수준에서 오디오/비디오 데이타에 대한 처리를 표현할 수 있다. DAViS는, 새로운 형식의 오디오/비디오 데이타를 처리하는 부분을 손쉽게 통합하고, 하부 네트워크의 전송기술이나 컴퓨터시스템 관련 기술의 진보를 신속하고 자연스럽게 수용할 수 있도록 하는 유연한 구조를 가지고 있다. Abstract This paper describes the design and implementation of software framework which supports the processing of real-time stream data like audio and video in distributed object-oriented computing environment. DAViS(Distributed Object Framework supporting Audio/Video Streaming), proposed in this paper, abstracts software components concerning the processing of audio/video data as distributed objects and separates the transmission path of data between them from that of control information. Based on DAViS, distributed applications can be written in the same abstract level as is provided by the existing distributed environment in handling audio/video data. DAViS has a flexible internal structure enough to easily incorporate new types of audio/video data and to rapidly accommodate the progress of underlying network and computer system technology with very little modifications.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.119-140
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• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.47-53
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• 2017

Recently, huge datasets have been generating rapidly in a variety of fields. Then, there is an urgent need for technologies that will allow efficient and effective processing of huge datasets. Therefore the problems of partitioning a huge dataset effectively and alleviating the processing overhead of the partitioned data efficiently have been a critical factor for scalability and performance in distributed database system. In our work we utilized multicore servers to provide scalable service to our distributed system. The partitioning of database over multicore servers have emerged from a need for new architectural design of distributed database system from scalability and performance concerns in today's data deluge. The system allows uniform access through a web service interface to concurrently distributed databases over multicore servers, using SQMD (Single Query Multiple Database) mechanism based on publish/subscribe paradigm. We will present performance results with the distributed database system built on multicore server, which is time intensive with traditional architectures. We will also discuss future works.