• Title/Summary/Keyword: cloud-based application

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Performance Test of Asynchronous Process of OGC WPS 2.0: A Case Study for Geo-based Image Processing

  • Yoon, Gooseon;Lee, Kiwon
    • Korean Journal of Remote Sensing
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    • v.33 no.4
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    • pp.391-400
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    • 2017
  • Geo-based application services linked with the Open Geospatial Consortium (OGC) Web Processing Service (WPS) protocol have been regarded as an important standardized framework for of digital earth building in the web environments. The WPS protocol provides interface standards for analysis functionalities within geo-spatial processing in web-based service systems. Despite its significance, there is few performance tests of WPS applications. The main motivation in this study is to perform the comparative performance test on WPS standards. Test system, which was composed of WPS servers, WPS framework, data management module, geo-based data processing module and client-sided system, was implemented by fully open source stack. In this system, two kinds of geo-based image processing functions such as cloud detection and gradient magnitude computation were applied. The performance test of different server environments of non-WPS, synchronous WPS 1.0 and asynchronous WPS 2.0 was carried out using 100 threads and 400 threads corresponds client users on a web-based application service. As the result, at 100 threads, performance of three environments was within an adjacent range in the average response time to complete the processing of each thread. At 400 threads, the application case of WPS 2.0 showed the distinguished characteristics for higher performance in the response time than the small threads cases. It is thought that WPS 2.0 contributes to settlement of without performance problems such as time delay or thread accumulation.

Performance Testing of Satellite Image Processing based on OGC WPS 2.0 in the OpenStack Cloud Environment (오픈스택 클라우드 환경 OGC WPS 2.0 기반 위성영상처리 성능측정 시험)

  • Yoon, Gooseon;Kim, Kwangseob;Lee, Kiwon
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.617-627
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    • 2016
  • Many kinds of OGC-based web standards have been utilized in the lots of geo-spatial application fields for sharing and interoperable processing of large volume of data sets containing satellite images. As well, the number of cloud-based application services by on-demand processing of virtual machines is increasing. However, remote sensing applications using these two huge trends are globally on the initial stage. This study presents a practical linkage case with both aspects of OGC-based standard and cloud computing. Performance test is performed with the implementation result for cloud detection processing. Test objects are WPS 2.0 and two types of geo-based service environment such as web server in a single core and multiple virtual servers implemented on OpenStack cloud computing environment. Performance test unit by JMeter is five requests of GetCapabilities, DescribeProcess, Execute, GetStatus, GetResult in WPS 2.0. As the results, the performance measurement time in a cloud-based environment is faster than that of single server. It is expected that expansion of processing algorithms by WPS 2.0 and virtual processing is possible to target-oriented applications in the practical level.

A study on Cloud Security based on Network Virtualization (네트워크 가상화 기반 클라우드 보안 구성에 관한 연구)

  • Sang-Beom Hong;Sung-Cheol Kim;Mi-Hwa Lee
    • Convergence Security Journal
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    • v.23 no.5
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    • pp.21-27
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    • 2023
  • In the cloud computing environment, servers and applications can be set up within minutes, and recovery in case of fail ures has also become easier. Particularly, using virtual servers in the cloud is not only convenient but also cost-effective compared to the traditional approach of setting up physical servers just for temporary services. However, most of the und erlying networks and security systems that serve as the foundation for such servers and applications are primarily hardwa re-based, posing challenges when it comes to implementing cloud virtualization. Even within the cloud, there is a growing need for virtualization-based security and protection measures for elements like networks and security infrastructure. This paper discusses research on enhancing the security of cloud networks using network virtualization technology. I configured a secure network by leveraging virtualization technology, creating virtual servers and networks to provide various security benefits. Link virtualization and router virtualization were implemented to enhance security, utilizing the capabilities of virt ualization technology. The application of virtual firewall functionality to the configured network allowed for the isolation of the network. It is expected that based on these results, there will be a contribution towards overcoming security vulnerabil ities in the virtualized environment and proposing a management strategy for establishing a secure network.

Cyclostorm : The Cloud Computing Service for Uplifting Javascript Processing Efficiency of Mobile Applications based on WAC (Cyclostorm : WAC 기반 모바일 앱의 자바스크립트 처리 효율 향상을 위한 클라우드 컴퓨팅 서비스)

  • Bang, Jiwoong;Kim, Daewon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.150-164
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    • 2013
  • Currently it is being gradually focused on the mobile application's processing performance implemented by Javascript and HTML (Hyper Text Markup Language) due to the dissemination of mobile web application supply based on the WAC (Wholesale Application Community). If the application software has a simple functional processing structure, then the problem is benign, however, the load of a browser is getting heavier as the amount of Javascript processing is being increased. There is a limitation on the processing time and capacity of the Javascript in the ordinary mobile browsers which are on the market now. In order to solve those problems, the Web Worker that is not supported from the existing Javascript technology is now provided by the HTML 5 to implement the multi thread. The Web Worker provides a mechanism that process a part from the single thread through a separate one. However, it can not guarantee the computing ability as a native application on the mobile and is not enough as a solution for improving the fundamental processing speed. The Cyclostorm overcomes the limitation of resources as a mobile client and guarantees the performance as a native application by providing high computing service and ascripting the Javascript process on the mobile to the computer server on the cloud. From the performance evaluation experiment, the Cyclostorm shows a maximally 6 times faster computing speed than in the existing mobile browser's Javascript and 3 to 6 times faster than in Web Worker of the HTML 5. In addition, the usage of memory is measured less than the existing method since the server's memory has been used. In this paper, the Cyclostorm is introduced as one of the mobile cloud computing services to conquer the limitation of the WAC based mobile browsers and to improve the existing web application's performances.

Cloud Platform for Smartfarm (스마트팜을 위한 클라우드 플랫폼)

  • Lee, Meong-hun;Yi, Se-yong;Kim, Joon-yong;Yoe, Hyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.496-499
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    • 2016
  • The smartfarm is a leader in the Field of environmental monitoring in agriculture. By the use of wireless remote systems, monitoring applications of the smartfarm are able to provide vital information to the farmer wherever he may be. Absentee farmers are finding the ease of viewing the application graphs on their mobile phone is providing them with peace of mind. We design system and technical requirements of service for managing and operating smart-farm based on cloud technology. It describes requirements of cloud technology for monitoring, controlling, managing, and operating cloud-based smart farm. Smart farm system and service with cloud platform contains 3 interfaces and 3 services. In addition, smart-farm using cloud platform could have several cases so it should be established and managed in varying way depending on cultivars, its size and type. This paper will focus the industry's attention on the importance of Open/Standard Cloud platform thereby stimulating the smartfarm in agriculture.

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Adaptive Cloud Offloading of Augmented Reality Applications on Smart Devices for Minimum Energy Consumption

  • Chung, Jong-Moon;Park, Yong-Suk;Park, Jong-Hong;Cho, HyoungJun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.8
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    • pp.3090-3102
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    • 2015
  • The accuracy of an augmented reality (AR) application is highly dependent on the resolution of the object's image and the device's computational processing capability. Naturally, a mobile smart device equipped with a high-resolution camera becomes the best platform for portable AR services. AR applications require significant energy consumption and very fast response time, which are big burdens to the smart device. However, there are very few ways to overcome these burdens. Computation offloading via mobile cloud computing has the potential to provide energy savings and enhance the performance of applications executed on smart devices. Therefore, in this paper, adaptive mobile computation offloading of mobile AR applications is considered in order to determine optimal offloading points that satisfy the required quality of experience (QoE) while consuming minimum energy of the smart device. AR feature extraction based on SURF algorithm is partitioned into sub-stages in order to determine the optimal AR cloud computational offloading point based on conditions of the smart device, wireless and wired networks, and AR service cloud servers. Tradeoffs in energy savings and processing time are explored also taking network congestion and server load conditions into account.

A Novel Framework for Resource Orchestration in OpenStack Cloud Platform

  • Muhammad, Afaq;Song, Wang-Cheol
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5404-5424
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    • 2018
  • This work is mainly focused on two major topics in cloud platforms by using OpenStack as a case study: management and provisioning of resources to meet the requirements of a service demanded by remote end-user and relocation of virtual machines (VMs) requests to offload the encumbered compute nodes. The general framework architecture contains two subsystems: 1) An orchestrator that allows to systematize provisioning and resource management in OpenStack, and 2) A resource utilization based subsystem for vibrant VM relocation in OpenStack. The suggested orchestrator provisions and manages resources by: 1) manipulating application program interfaces (APIs) delivered by the cloud supplier in order to allocate/control/manage storage and compute resources; 2) interrelating with software-defined networking (SDN) controller to acquire the details of the accessible resources, and training the variations/rules to manage the network based on the requirements of cloud service. For resource provisioning, an algorithm is suggested, which provisions resources on the basis of unused resources in a pool of VMs. A sub-system is suggested for VM relocation in a cloud computing platform. The framework decides the proposed overload recognition, VM allocation algorithms for VM relocation in clouds and VM selection.

Study on Enhancement of Data Processing Algorithm in SaaS Cloud Infrastructure to Monitor Wind Turbine Condition (풍력발전기 상태 감시를 위한 SaaS 클라우드 인프라 내 데이터 처리 알고리즘 개선 연구)

  • Lee, Gwang-Se;Choi, Jungchul;Kang, Minsang;Park, Sail;Lee, JinJae
    • New & Renewable Energy
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    • v.16 no.1
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    • pp.25-30
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    • 2020
  • In this study, an SW for the analysis of the wind-turbine vibration characteristics was developed as an application of SaaS cloud infrastructure. A measurement system for power-performance, mechanical load, and gearbox vibration as type-test class was installed at a target MW-class wind turbine, and structural meta and raw data were then acquired into the cloud. Data processing algorithms were developed to provide cloud data to the SW. To operate the SW continuously, raw data was downloaded consistently based on the algorithms. During the SW test, an intermittent long time-delay occurred due to the communication load associated with frequent access to the cloud. To solve this, a compression service for the target raw data was developed in the cloud and more stable data processing was confirmed. Using the compression service, stable big data processing of wind turbines, including gearbox vibration analysis, is expected.

A Study on the Proposal of the Cloud Based Technology for VoD Systems and Analysis of Economic Effects (양식VoD 시스템에 대한 클라우드 기반 기술을 적용 제안 및 경제적인 효과를 분석 연구)

  • Chae, Jong Soo;Byeon, Sang-Gu;Seo, Chang-Ho;Yang, Jong Won
    • Journal of Korea Entertainment Industry Association
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    • v.5 no.1
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    • pp.149-153
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    • 2011
  • In this study, a configuration method for a cloud technology based VoD system through two different scenarios is proposed. The first scenario virtualizes DMC, content storages for each SO, and stream servers in the conventional VoD system in order to efficiently use the additionally required storage capacity and stream server. In the second scenario, it is proposed that cable broadcasting systems including VoD systems are to be changed as cloud in which the subscriber STB should have minimum programs and storage regions to connect networks, and the operating system and middle ware presented in the existing subscriber STB is moved to the cloud data center. In addition, the comparison of the application of the cloud technology for the cost of changing the existing system to STB and the cost of establishing a cloud VoD system is performed in order to analyze the cost reduction in broadcasting businesses based on the establishment of VoD systems.

Scaling of Hadoop Cluster for Cost-Effective Processing of MapReduce Applications (비용 효율적 맵리듀스 처리를 위한 클러스터 규모 설정)

  • Ryu, Woo-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.1
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    • pp.107-114
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    • 2020
  • This paper studies a method for estimating the scale of a Hadoop cluster to process big data as a cost-effective manner. In the case of medical institutions, demands for cloud-based big data analysis are increasing as medical records can be stored outside the hospital. This paper first analyze the Amazon EMR framework, which is one of the popular cloud-based big data framework. Then, this paper presents a efficiency model for scaling the Hadoop cluster to execute a Mapreduce application more cost-effectively. This paper also analyzes the factors that influence the execution of the Mapreduce application by performing several experiments under various conditions. The cost efficiency of the analysis of the big data can be increased by setting the scale of cluster with the most efficient processing time compared to the operational cost.