• Electronics and Telecommunications Trends
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• v.39 no.3
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• pp.69-78
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• 2024

Cloud computing technology based on centralized high-performance computing has brought about major changes across the information technology industry and led to new paradigms. However, with the rapid development of the industry and increasing need for mass generation and real-time processing of data across various fields, centralized cloud computing is lagging behind the demand. This is particularly critical in emerging technologies such as autonomous driving, the metaverse, and augmented/virtual reality that require the provision of services with ultralow latency for real-time performance. To address existing limitations, distributed and edge cloud computing technologies have recently gained attention. These technologies allow for data to be processed and analyzed closer to their point of generation, substantially reducing the response times and optimizing the network bandwidth usage. We describe distributed and edge cloud computing technologies and explore the latest trends in their standardization.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.55-61
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• 2017

Cloud computing is cost-effective in terms of system configuration and maintenance and does not require special IT skills for management. Also, cloud computing provides an access control setting where SSO is adopted to secure user convenience and availability. As the SSO user authentication structure of cloud computing is exposed to quite a few external security threats in wire/wireless network integrated service environment, researchers explore technologies drawing on distributed SSO agents. Yet, although the cloud computing access control using the distributed SSO agents enhances security, it impacts on the availability of services. That is, if any single agent responsible for providing the authentication information fails to offer normal services, the cloud computing services become unavailable. To rectify the environment compromising the availability of cloud computing services, and to protect resources, the current paper proposes a security policy that controls the authority to access the resources for cloud computing services by applying the authentication policy of user authentication agents. The proposed system with its policy of the authority to access the resources ensures seamless and secure cloud computing services for users.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.70-71
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• 2017

Volunteer Computing은 대규모 프로젝트를 많은 분산된 데스크탑, 랩탑 PC, 그리고 스마트 폰과 같은 모바일 디바이스의 idle(유휴 상태)인 컴퓨팅 자원을 기여(Volunteer)받아 수행하는 환경이다. 그러나 기여된 컴퓨팅 자원이 idle과 used(사용 상태) 간의 상태전이가 빈번히 일어나거나, idle로 지속되는 시간이 짧은 자원의 경우, 프로젝트를 수행하는데 비효율적이다. 따라서 본 논문에서는 이러한 자원을 구분하고, 해당 자원의 다음 상태전이확률테이블을 계산하여 결과에 따라 해당 자원에 적합한 작업을 할당하는 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.102-105
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• 2013

최근 멀티코어 시스템은 컴퓨터의 성능을 향상시키기 위해 더 많은 수의 코어를 연결시키는 다중코어 시스템으로 발전하고 있다. 그러나 멀티코어 시스템은 사용하는 코어의 아키텍처 구조와 개수에 따라 성능 차이가 발생한다. 이에, 본 논문에서는 코어의 아키텍처 구조와 코어의 개수가 성능에 미치는 영향을 분석하기 위해 Tilera의 다중코어 시스템인 Tile-Gx36, TilePro64와 Intel의 x86-64 멀티코어 시스템인 Core i5의 성능을 비교하였다. 코어의 사용률이 늘어남에 따른 성능차이를 알아보기 위해 벤치마크 프로그램인 SPEC CPU 2006을 이용하여 각 시스템 내 단일코어의 성능을 측정하고, OpenMP 벤치마크 프로그램을 이용하여 시스템의 모든 코어를 사용했을 때의 입력 데이터 크기에 따른 성능을 측정하였다. 실험 결과, 단일코어에서의 성능은 정수형 데이터를 사용하여 측정하였을 경우 Core i5가 Tile-Gx36보다 약 87%, 실수형 데이터를 사용하여 측정하였을 경우 약 94% 더 빠른 것으로 나타났다. 그러나 코어 전체를 이용한 성능 결과에서는 정수형 배열 크기가 이상일 경우 Tile-Gx36 시스템의 처리 속도가 Core i5 시스템 보다 평균적으로 약 7.6배 향상됨을 확인할 수 있었다. 따라서 Tilera의 다중코어 시스템은 클럭 속도와 아키텍처 구조의 영향으로 단일코어의 성능은 떨어지나, 병렬 처리를 이용한 고속연산에서는 성능이 향상된다고 할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.67-74
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• 2016

Distributed agile software development faces difficulties for instance lack of visibility across development and delivery processes, complex and disjointed development processes, inability to capitalize on business opportunities, lack of communication agility between disconnected owners, development teams, and users or clients. However these difficulties are solved with the help of cloud computing services. This study proposes a framework to provide a skeletal or structural environment for distributed agile software development in cloud computing environment. The framework guide towards the best tooling to deliver a consistent, automated, governed, and unified agile software development process with reduced technical debt, and minimized project backlog. In addition to this, the study highlights the benefits of cloud computing in agile software development.

• Spatial Information Research
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• v.19 no.4
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• pp.55-71
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• 2011

Recently, interest in cloud computing which provides IT resources as service form in IT field is increasing. As a result, much research has been done on the distributed data processing that store and manage a large amount of data in many servers. Meanwhile, in order to effectively utilize the spatial data which is rapidly increasing day by day with the growth of GIS technology, distributed processing of spatial data using cloud computing is essential. Therefore, in this paper, we review the representative distributed data processing techniques and we analyze the optimization requirements for performance improvement of the distributed processing techniques for a large amount of data. In addition, we uses the Hadoop and we evaluate the performance of the distributed data processing techniques for their optimization requirements.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.989-998
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• 2011

Cloud computing provides computation, software, data access, and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a group quorum system (GQS)-based dissemination for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed GQS-based method organizes these distributed clouds into a group quorum ring overlay to support a constant event dissemination latency. Our numerical results show that the GQS-based method improves the efficiency as compared with Chord-based and Plume methods.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.30-39
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• 2012

In these day, some of IT venders already were going to cloud computing market, as well they are going to expand their territory for the cloud computing market through that based on their hardware and software technology, making collaboration between hardware and software vender. Distributed file system is very mainly technology for the cloud computing that must be protect performance and safety for high levels service requests as well data store. This paper introduced distributed file system for cloud computing and how to use this theory such as memory database, Hadoop file system, high availability database system. now In the market, this paper define a very large distributed processing architect as a reference by kind of distributed file systems through using technology in cloud computing market.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1259-1269
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• 2012

Cloud computing has rapidly become a new infrastructure for organizations to reduce their capital cost in IT investment and to develop planetary-scale distributed applications. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a geographic group quorum system (GGQS)-based hybrid algorithm for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed algorithm first organizes these distributed clouds into a geographic group quorum overlay to support a constant event dissemination latency. Then it uses a hybrid protocol that combines geographic group-based broad-cast with quorum-based multicast. Our numerical results show that the GGQS-based hybrid algorithm improves the efficiency as compared with Chord-based, Plume an GQS-based algorithms.