• Title/Summary/Keyword: Cloud ecosystem

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An Intelligent Machine Learning Inspired Optimization Algorithm to Enhance Secured Data Transmission in IoT Cloud Ecosystem

  • Ankam, Sreejyothsna;Reddy, N.Sudhakar
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.83-90
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    • 2022
  • Traditional Cloud Computing would be unable to safely host IoT data due to its high latency as the number of IoT sensors and physical devices accommodated on the Internet grows by the day. Because of the difficulty of processing all IoT large data on Cloud facilities, there hasn't been enough research done on automating the security of all components in the IoT-Cloud ecosystem that deal with big data and real-time jobs. It's difficult, for example, to build an automatic, secure data transfer from the IoT layer to the cloud layer, which incorporates a large number of scattered devices. Addressing this issue this article presents an intelligent algorithm that deals with enhancing security aspects in IoT cloud ecosystem using butterfly optimization algorithm.

A Development of Cloud Service Partner Competency Analysis Framework (클라우드 서비스 파트너 역량 분석 프레임워크 개발)

  • Park, Wonju;Seo, Kwang-Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.3
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    • pp.69-73
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    • 2022
  • The application of cloud computing to many industrial domains is rapidly increasing, and domestic and foreign cloud service providers are actively conducting business. In the domestic cloud market, it is necessary to establish an ecosystem with partner operators that work closely with private cloud service providers. In this paper, to create such an environment, we propose a framework that can evaluate the capabilities of partners required for cloud service providers to establish specific business strategies. The framework proposed in this study establishes criteria for evaluating partners' competencies and applies a decision-making model such as fuzzy AHP for evaluation. Eventually this will help not only to expand the domestic cloud market but also to strengthen the competitiveness of domestic cloud partners through the growth of the domestic cloud market.

A Case Study of Collaboration in Cloud Service Ecosystem: Focus on Cloud Service Brokerage (클라우드 서비스 생태계 내의 협업 사례 연구: 클라우드 서비스 중개업을 중심으로)

  • Kim, Kitae;Kim, Jong Woo
    • Information Systems Review
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    • v.17 no.1
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    • pp.1-18
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    • 2015
  • Recently, the number of available cloud services are increasing dramatically because many IT companies have entered into cloud service market. Due to the reason, cloud service brokers are emerging as agents to solve cloud service selection problems and to support cloud service initialization and maintenance of unskilled cloud service users. In this study, NCloud24 case in South Korea and Right Scale case in the USA are analyzed as representative examples of the collaboration between original cloud service providers and cloud service brokers. The business models of two companies are analyzed using Business Model Canvas. The emergence of cloud service brokers are interpreted as unbundling process of IaaS (Infrastructure-as-a-service) cloud service companies. Based on the comparison with the two companies, we prospect future directions of cloud service brokerage.

Building a Sustainable UX Ecosystem under N-Screen and Cloud Computing Paradigm (N-Screen과 클라우드 컴퓨팅 패러다임에서의 지속가능한 UX 생태계 구축에 대한 연구)

  • Kim, Sung-Woo
    • Journal of the Ergonomics Society of Korea
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    • v.29 no.4
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    • pp.553-561
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    • 2010
  • This paper discusses the next direction for user experience design to keep pace with an ongoing IT paradigm shift, particularly focused on UX standardization activity contributing to reinforcement of brand power and customer loyalty. The paper introduces a model that identifies four levels of UX standardization and a key concept called "sustainable UX ecosystem" as its top level. It argues that in the new IT paradigm the fourth level of UX standardization, the sustainable UX ecosystem, is the next direction user experience must head towards.

Open Cloud Platform Ecosystem Strategy Using the Container Orchestration Platform (컨테이너 자동편성 플랫폼을 활용한 개방형 클라우드 플랫폼 생태계 전략)

  • Jung, Ki-Bong;Hyun, Jae-Uk;Yoon, Hee-Geun;Kim, Eun-Ju
    • Informatization Policy
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    • v.26 no.3
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    • pp.90-106
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    • 2019
  • The cloud services market is growing rapidly from the on-premises environment to the cloud computing environment and the domestic cloud software market in Korea is expected to grow at a CAGR of around 15%. In Korea, research teams are providing open cloud platforms using open source software under the government taking the initiative, which intends to enhance the reliability and functionality of open cloud platforms, provide users with a world-class open cloud platform-based and developer-friendly environment that is managed on heterogeneous cloud infrastructure and supported by full-lifecycle management of application software. In this paper, we propose a method to utilize CaaS in the open cloud platform, through incorporating the platform with the container orchestration platform. Finally, by providing users with the application runtime and container runtime, it presents how the two platforms can coexist and cooperate in the same ecosystem.

Examining the Generative Artificial Intelligence Landscape: Current Status and Policy Strategies

  • Hyoung-Goo Kang;Ahram Moon;Seongmin Jeon
    • Asia pacific journal of information systems
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    • v.34 no.1
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    • pp.150-190
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    • 2024
  • This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

AI Platform Solution Service and Trends (글로벌 AI 플랫폼 솔루션 서비스와 발전 방향)

  • Lee, Kang-Yoon;Kim, Hye-rim;Kim, Jin-soo
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.9-16
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    • 2017
  • Global Platform Solution Company (aka Amazon, Google, MS, IBM) who has cloud platform, are driving AI and Big Data service on their cloud platform. It will dramatically change Enterprise business value chain and infrastructures in Supply Chain Management, Enterprise Resource Planning in Customer relationship Management. Enterprise are focusing the channel with customers and Business Partners and also changing their infrastructures to platform by integrating data. It will be Digital Transformation for decision support. AI and Deep learning technology are rapidly combined to their data driven platform, which supports mobile, social and big data. The collaboration of platform service with business partner and the customer will generate new ecosystem market and it will be the new way of enterprise revolution as a part of the 4th industrial revolution.

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An Exploratory Study on the Cloud Computing Services: Issues and Suggestion for The Success

  • Lee, Jong Un;Seo, Kyung Jin;Kim, Hee-Woong
    • Asia pacific journal of information systems
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    • v.24 no.4
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    • pp.473-491
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    • 2014
  • There is a growing interest for 'Cloud computing' to cut costs, and help the users focus on their core business instead of being impeded by IT obstacles. As it became IT version 3.0 which represents the era of cloud services and the dominance of a new kind of IT service provider, cloud service providers (CSPs)' role is more critical as a trusted IT advisor to include cloud migration and integration expertise. However, previous literatures related to cloud computing service have mainly analyzed from customers, although it is hard for customers to totally understand the complex and diverse cloud ecosystem. Therefore, it is an urgent task to mitigate the inhibitory factors in providing the cloud services for activating cloud industry. This study, an exploratory research based on interviews, has derived factors of promoting and hindering the activation of cloud computing from the provider's perspective, and has analyzed a sequence of cause and effect for each factor. For this, the casual loop diagram was developed to deduce key issues, and propose an alternative. The results of this study are expected to help activate 'Cloud computing' in Korea by minimizing the potential negative effects of activating 'Cloud computing' industry.

Analysis of Future Spectrum Sharing Ecosystem Based on Causal Map (인과지도에 기반한 미래 주파수공유 생태계 분석)

  • Song, Hee Seok;Kim, Taehan
    • Journal of Information Technology Applications and Management
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    • v.20 no.4
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    • pp.19-31
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    • 2013
  • There is tremendous increasing demand on spectrum resource which is boosted by spread of cloud computing and M2M telecommunication as well as smart phone and tablet PC. Recently, spectrum sharing technology has drawn attention to the spectrum policy makers as a promising way to overcome limitation of scarce spectrum resource. To succeed in commercialization of spectrum sharing technology, it is necessary to prospect the future business ecosystem of spectrum sharing and develop appropriate policies and laws at the same time along with the advance of spectrum sharing technology. The purpose of this paper is to prospect future spectrum sharing ecosystem and analyze business ecosystem of spectrum sharing with casual loop map. With the causal map and system dynamics method, it is possible to analyze feedback loops which is not limited to linear thinking and build policies which optimize positive dynamics in business ecosystem of spectrum sharing.

Cloud computing for handling data from traffic sensing technologies and on-board diagnostics

  • Nkenyereye, Lionel;Jang, Jong-wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.488-491
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    • 2014
  • Based on a complete understanding research in Information and Communication Technologies (ICT), the Intelligent Transport Systems rapidly build up innovative applications to ensure real time attainment as well remote management of driven information, provide a huge range of services and involve many actors in automotive ecosystem. In this paper, we present an intelligent cloud computing for handling data received from traffic sensing technologies. Transportations technologies applied in ITS have played a great role in collecting data from devices deployed in vehicles and highway infrastructures utilizing broadband wireless technologies to the Cloud. In order to facilitate the interested in automotive industry to use data collected and afford services to the car's owner, a scalable acquisition, access to computing resources and offered services are the primary goal of the proposed cloud computing.

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