• Title/Summary/Keyword: Cloud modeling

Search Result 264, Processing Time 0.023 seconds

A Layered Protection System for a Cloud Storage of Defense M&S Resources (국방 재사용 자원의 클라우드 저장소를 위한 계층형 보호 시스템)

  • Park, Chanjong;Han, Seungchul;Lee, Kangsun
    • 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.

A study of Modeling and Simulation for the Availability Optimization of Cloud Computing Service (클라우드 컴퓨팅 서비스의 가용성 최적화를 위한 모델링 및 시뮬레이션)

  • Jang, Eun-Young;Park, Choon-Sik
    • Journal of the Korea Society for Simulation
    • /
    • v.20 no.1
    • /
    • pp.1-8
    • /
    • 2011
  • Cloud computing emerges as a new paradigm for deploying, managing and offering IT resources as a service anytime, anywhere on any devices. Cloud computing data center stores many IT resources through resource integration. So cloud computing system has to be designed by technology and policy to make effective use of IT resources. In other words, cloud vendor has to provide high quality services to all user and mitigate the dissipation of IT resources. However, vendors need to predict the performance of cloud services and the use of IT resources before releasing cloud service. For solving the problem, this research presents cloud service modeling on network environment and evaluation index for availability optimization of cloud service. We also study how to optimize an amount of requested cloud service and performance of datacenter using CloudSim toolkit.

Depth-based Mesh Modeling for Virtual Environment Generation (가상 환경 생성을 위한 깊이 기반 메쉬 모델링)

  • 이원우;우운택
    • Proceedings of the IEEK Conference
    • /
    • 2003.11b
    • /
    • pp.111-114
    • /
    • 2003
  • In this paper, we propose a depth-based mesh modeling method to generate virtual environment. The proposed algorithm constructs mesh model from unorganized point cloud obtained from a multi-view camera. We separate the point cloud consisting objects from the background. Then, we apply triangulation to each object and background. Since the objects and the background are modeled independently, it is possible to construct effective virtual environment. The application of proposed modeling method is applicable to entertainment, such as movie and video game and effective virtual environment generation.

  • PDF

Performance Optimization of Numerical Ocean Modeling on Cloud Systems (클라우드 시스템에서 해양수치모델 성능 최적화)

  • JUNG, KWANGWOOG;CHO, YANG-KI;TAK, YONG-JIN
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.27 no.3
    • /
    • pp.127-143
    • /
    • 2022
  • Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

K-Defense Cloud Computing System Design through Cloud Modeling and Analysis of Social Network Service Application (소셜 네트워크 서비스 어플리케이션의 클라우드 모델링 및 분석을 통한 국방 클라우드 컴퓨탱 시스템 설계)

  • Lee, Sung-Tae;Ryou, Hwang-Bin
    • Convergence Security Journal
    • /
    • v.13 no.1
    • /
    • pp.37-43
    • /
    • 2013
  • In 2010, the Ministry of National Defense decided to build a MegaCenter including the cloud computing technology by 2014, as part of the '2012 Information Service Plan', which is now underway. The Cloud computing system environment should be designed applying cloud computing technology and policy for an efficient infrastructure that many IT resources are available in the data center as a concentrated form. That is, the system should be designed in such a way that clouding services will be efficiently provided to meet the needs of users and there will not be unnecessary waste of resources. However, in order to build an optimal system, it should be possible to predict the service performance and the resource availability at the initial phase of system design. In this paper, using the CloudAnalyst simulator to predict availability of the K-defence cloud computing system service, conducts cloud modeling and analysis of the 'Facebook', one of the most famous social network service applications with most users in the world. An Optimal K-Defense cloud computing design model is proposed through simulation results.

Scan-to-Geometry Mapping Rule Definition for Building Plane Reverse engineering Automation (건축물 평면 형상 역설계 자동화를 위한 Scan-to-Geometry 맵핑 규칙 정의)

  • Kang, Tae-Wook
    • Journal of KIBIM
    • /
    • v.9 no.2
    • /
    • pp.21-28
    • /
    • 2019
  • Recently, many scan projects are gradually increasing for maintenance, construction. The scan data contains useful data, which can be generated in the target application from the facility, space. However, modeling the scan data required for the application requires a lot of cost. In example, the converting 3D point cloud obtained from scan data into 3D object is a time-consuming task, and the modeling task is still very manual. This research proposes Scan-to-Geometry Mapping Rule Definition (S2G-MD) which maps point cloud data to geometry for irregular building plane objects. The S2G-MD considers user use case variability. The method to define rules for mapping scan to geometry is proposed. This research supports the reverse engineering semi-automatic process for the building planar geometry from the user perspective.

Load Balancing in Cloud Computing Using Meta-Heuristic Algorithm

  • Fahim, Youssef;Rahhali, Hamza;Hanine, Mohamed;Benlahmar, El-Habib;Labriji, El-Houssine;Hanoune, Mostafa;Eddaoui, Ahmed
    • Journal of Information Processing Systems
    • /
    • v.14 no.3
    • /
    • pp.569-589
    • /
    • 2018
  • Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.

A Study on The Construction of Cloud BIM-based Medical Facility Design Support System (클라우드 BIM 기반 의료시설 설계지원 시스템 구축에 관한 연구)

  • Jung, Sung-Ho;Lee, Byung-Soo;Choi, Yoon-Ki
    • Journal of the Architectural Institute of Korea Planning & Design
    • /
    • v.35 no.6
    • /
    • pp.39-46
    • /
    • 2019
  • In the 21st century, medical facility projects are required to operate appropriate digital technologies as the development of technology and the interests of various participants become more complex. In order for architects to successfully lead negotiations among various stakeholder groups, it is necessary to plan for effective communication through appropriate design reflecting their opinions and coordination of conflicts. For this purpose, building information modeling (BIM), which is a method of designing based on knowledge information related to medical facilities in the building database, can respond to change of order promptly and minimizes the occurrence of design errors can do. Recently, BIM technology and cloud computing technology in ICT have been combined and research on cloud BIM has been actively carried out. The use of cloud computing technology in BIM-based healthcare facility projects can effectively support decision making among project participants and has the advantage of sharing and collaborating on various forms of information generated during the design process, regardless of location and time. Therefore, the purpose of this study is to build of system that can support the design of medical facility using cloud computing technology in BIM.

IP-CCTV Risk Decision Model Using AHP (Cloud Computing Based) (AHP를 활용한 IP-CCTV 위험 결정 모델 (클라우드 컴퓨팅 기반으로))

  • Jung, Sung-hoo;Lee, Kyung-ho
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.28 no.1
    • /
    • pp.229-239
    • /
    • 2018
  • This paper analyzes the problems of existing CCTV and discusses cyber security problems of IP-CCTV in cloud computing environment. In order to reduce the risk of simply removing the risk associated with the provision of cloud services, the risk analysis and counter-measures need to be carried out effectively. Therefore, the STRIDE model as the Threat Risk Modeling is used to analyze the risk factors, and Analytic Hierarchy Process(AHP) is used to measure risk priorities based on the analyzed threats.

An Ontology-based Cloud Storage for Reusing Weapon Models (무기체계 모델 재사용을 위한 온톨로지 기반 클라우드 저장소 연구)

  • Kim, Tae-Sup;Park, Chan-Jong;Kim, Hyun-Hwi;Lee, Kang-Sun
    • Journal of the Korea Society for Simulation
    • /
    • v.21 no.3
    • /
    • pp.35-42
    • /
    • 2012
  • Defense Modeling and Simulation aims to provide a computerized war environment where we can analyze weapon systems realistically. As we invest significant efforts to represent weapon systems and their operational environments on the computer, there has been an increasing need to reuse predefined weapon models. In this paper, we introduce OB-Cloud (Ontology-Based Cloud storage) to utilize predefined weapon models. OB-Cloud has been implemented as a repository for OpenSIM (Open Simulation engine for Interoperable Models), which is an integrated simulation environment for aiding weapons effectiveness analysis, under the development of our research team. OB-Cloud uses weapon ontology and thesaurus dictionaries to provide semantic search for reusable models. In this paper, we present repository services of OB-Cloud, including registration of weapon models and semantic retrieval of similar models, and illustrate how we can improve reusability of weapon models, through an example.