• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• 인터넷정보학회논문지
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• 제19권3호
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• pp.57-66
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• 2018

계산과학공학 소프트웨어 플랫폼인 EDISON( EDucation-research Integration through Simulation On the Net )은 클라우드 컴퓨팅 기반 웹서비스로서, 해석 소프트웨어를 이용한 웹 기반 시뮬레이션 서비스이다. EDISON에서는 사용자의 로컬 자원으로는 해석이 어렵거나 불가능한 계산과학공학 해석 문제를 웹 서비스를 통해 사용자에게 제공하며 미리 구축되어 있는 인프라 및 다양한 계산 노드를 통해 사용자에게 해석 결과를 제공한다. 그 결과로 사용자의 디바이스, 운영체제에 관계 없이 EDISON에 접근하여 계산과학 공학 해석 시뮬레이션을 수행할 수 있도록 웹 포털 환경에서 시뮬레이션 실행 환경을 제공한다. 본 연구의 목적은 현재 사용자에게 제공되고 있는 계산과학 공학 시뮬레이션 및 해석 결과 분석 플랫폼인 EDSION 시스템에 통합적인 유저 인터페이스를 제공하기 위한 워크벤치 기반 실시간 동적 서비스 설계 및 구축에 있다. 또한 로컬에서 사용하는 계산과학공학 시뮬레이션 소프트웨어 환경과 유사한 사용자 유저 인터페이스를 가지며 다양한 해석기와 전처리기, 해석 시뮬레이션 소프트웨어 등의 동적인 웹 환경을 구성할 수 있는 워크벤치 기반 사용자 시뮬레이션 서비스 환경 구성에 대해 고안하였다. 이러한 웹 서비스를 제공하기 위해 사용자에게 필요한 서비스를 포틀릿 단위로 구성하였으며, 그 결과로 워크벤치를 이용한 시뮬레이션 서비스를 구축하였다.

• 한국컴퓨터그래픽스학회논문지
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• 제21권3호
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• pp.36-45
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• 2015

대용량 볼륨 데이터로부터 연속적인 고화질 영상을 생성하는 것은 공학이나 자연과학 분야에서 중요한 연구주제이다. 최신 가시화 기법을 이용해 고해상도데이터의 시각적 영상 정보를 효과적으로 보여줌으로써 데이터에 내재된 유용한 정보의 분석을 돕는 소프트웨어의 필요성이 증대되고 있다. 본 논문에서는 관측, 예측을 통해 구축된 지구환경 데이터를 효과적으로 분석, 표출하기 위해 클라이언트-서버기반의멀티플랫폼가시화시스템을설계했다.클러스터로구성된가시화서버는병렬/분산 처리를 통해 데이터를 클라이언트에게 전달하고, 클라이언트는 다양한 플랫폼에서 구동되도록 개발되었다. 개발된 클라이언트는 멀티 터치, 센서를 통해 직관적인 구동이 가능하고, 영상기반조명 기법의 적용으로 사실적인 렌더링을 지원한다.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.129-139
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• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.

• 한국정보처리학회논문지
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• 제6권9호
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• pp.2320-2331
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• 1999

본 연구에서는 한정된 자원만을 사용하는 기존의 워크스테이션 클러스터링 환경의 제한성을 극복하기 위하여 인터넷에 연결된 혼합 이기종 컴퓨터들을 병렬 컴퓨팅 플랫폼으로 활용하고자 하는 인터넷 컴퓨팅 환경의 구축 기법을 제안한다. 제안하는 글로벌 인터넷 컴퓨팅 환경(Global Internet Computing Environment)은 프로그램의 용이성, 이기종 지원의 효율성, 시스템의 확장성, 그리고 시스템 성능에 초점을 두고 자바를 프로그래밍 및 수행 환경으로 채택하여 인터넷 컴퓨팅 구축에 있어 필수적인 동적 자원 중계 및 관리, 효율적인 병렬 테스크 수행 기법을 제시한다. 본 논문에서는 제안하는 글로벌 인터넷 컴퓨팅 환경의 구성모델 및 동작모델 그리고 시험시스템 구축 내용 및 벤치마킹을 통한 성능 평가 결과를 제시하며 이를 바탕으로 인터넷 컴퓨팅 환경의 구축 개념, 복잡성, 성능의 문제에 대한 분석결과를 기술한다.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.239-251
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• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• Advances in aircraft and spacecraft science
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• 제4권3호
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• Advances in aircraft and spacecraft science
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• 제4권3호
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• pp.317-334
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

• 인터넷정보학회논문지
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• 제24권2호
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• pp.1-10
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• 2023

The Multi-access Edge Computing (MEC) paradigm equips network edge telecommunication infrastructure with cloud computing resources. It seeks to transform the edge into an IT services platform for hosting resource-intensive and delay-stringent services for mobile users, thereby significantly enhancing perceived service quality of experience. However, erratic user mobility impedes seamless service continuity as well as satisfying delay-stringent service requirements, especially as users roam farther away from the serving MEC resource, which deteriorates quality of experience. This work proposes a deep reinforcement learning based service mobility management approach for ensuring seamless migration of service instances along user mobility. The proposed approach focuses on the problem of selecting the optimal MEC resource to host services for high mobility users, thereby reducing service migration rejection rate and enhancing service availability. Efficacy of the proposed approach is confirmed through simulation experiments, where results show that on average, the proposed scheme reduces service delay by 8%, task computing time by 36%, and migration rejection rate by more than 90%, when comparing to a baseline scheme.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제6권10호
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• pp.407-414
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• 2017

다수의 태스크로 구성된 돈사 감시 응용은 내재된 데이터 병렬성을 활용하고 성능가속기를 사용하여 병렬 처리가 가능하다. 본 논문에서는 멀티코어 CPU와 매니코어 GPU로 구성된 이기종 컴퓨팅 플랫폼에서 돈사 감시 응용 수행 시 태스크 분배 방법을 제안한다. 즉, 각 태스크별로 OpenCL을 이용한 병렬 프로그램을 작성한 뒤, deviceCPU와 deviceGPU 각각에서 수행시켜 측정된 수행시간을 기준으로 가장 적합한 처리기를 결정한다. 제안 방법은 간단하지만 매우 효과적이고, CPU와 GPU로 구성된 이기종 컴퓨팅 플랫폼에서 다수의 태스크로 구성된 다른 응용을 병렬화하는 경우에도 적용될 수 있다. 실험 결과, 상이한 이기종 컴퓨팅 플랫폼에서 최적의 태스크 분배로 수행한 경우 가 전체 태스크들을 deviceGPU에서 수행한 GPU-only 방법에 비교하여 각각 2.7배, 8.7배, 2.7배 성능 개선이 되었음을 확인하였다.