• 제목/요약/키워드: Cloud Service Providers

검색결과 155건 처리시간 0.024초

UEPF:A blockchain based Uniform Encoding and Parsing Framework in multi-cloud environments

  • Tao, Dehao;Yang, Zhen;Qin, Xuanmei;Li, Qi;Huang, Yongfeng;Luo, Yubo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권8호
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    • pp.2849-2864
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    • 2021
  • The emerging of cloud data sharing can create great values, especially in multi-cloud environments. However, "data island" between different cloud service providers (CSPs) has drawn trust problem in data sharing, causing contradictions with the increasing sharing need of cloud data users. And how to ensure the data value for both data owner and data user before sharing, is another challenge limiting massive data sharing in the multi-cloud environments. To solve the problems above, we propose a Uniform Encoding and Parsing Framework (UEPF) with blockchain to support trustworthy and valuable data sharing. We design namespace-based unique identifier pair to support data description corresponding with data in multi-cloud, and build a blockchain-based data encoding protocol to manage the metadata with identifier pair in the blockchain ledger. To share data in multi-cloud, we build a data parsing protocol with smart contract to query and get the sharing cloud data efficiently. We also build identifier updating protocol to satisfy the dynamicity of data, and data check protocol to ensure the validity of data. Theoretical analysis and experiment results show that UEPF is pretty efficient.

클라우드를 이용한 중소기업정보화 경영혁신플랫폼의 오픈 마켓 전략 연구 (Open Market Strategy of the Business Innovation Platform for SME Informatization based on Cloud Computing)

  • 한현수;양희동;김기호
    • 한국IT서비스학회지
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    • 제14권4호
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    • pp.15-30
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    • 2015
  • SMBA (Small and Medium Business Administration) and TIPA (Korea Technology and Information Promotion Agency for SMEs) have operated the Business Innovation Platform for SME Informatization based on cloud computing technology with the cooperation of seven industry cooperatives since 2013. This project will evolve into the open market platform where service providers and users voluntarily participate and transact. This research conducts the literature review about the concept of open market and the empirical analysis through survey for the software providers and the future users regarding the future operation methods. The policy about how the open market strategy for the business innovation platform needs to be designed and implemented are organized as the three differentiated government support strategies. The first is to provide free IT services including specialized core operation support S/W which is developed only for the small or home office group of firms which lack minimal informatization capability and budget. The second is to augment IT platform service through incorporating ERP supplier initiated commercial S/W sales window for those firms having medium level informatization capability. This includes to provide IT support for customization and system integration with existing government subsidized S/W. The third is to provide upgrading services of existing S/W functions to facilitate better system utilization. The results provide useful insight for government role to enhance SME competitiveness using IT.

An Anti-Overload Model for OpenStack Based on an Effective Dynamic Migration

  • Ammar, Al-moalmi;Luo, Juan;Tang, Zhuo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4165-4187
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    • 2016
  • As an emerging technology, cloud computing is a revolution in information technology that attracts significant attention from both public and private sectors. In this paper, we proposed a dynamic approach for live migration to obviate overloaded machines. This approach is applied on OpenStack, which rapidly grows in an open source cloud computing platform. We conducted a cost-aware dynamic live migration for virtual machines (VMs) at an appropriate time to obviate the violation of service level agreement (SLA) before it happens. We conducted a preemptive migration to offload physical machine (PM) before the overload situation depending on the predictive method. We have carried out a distributed model, a predictive method, and a dynamic threshold policy, which are efficient for the scalable environment as cloud computing. Experimental results have indicated that our model succeeded in avoiding the overload at a suitable time. The simulation results from our solution remarked the very efficient reduction of VM migrations and SLA violation, which could help cloud providers to deliver a good quality of service (QoS).

A Bi-objective Game-based Task Scheduling Method in Cloud Computing Environment

  • Guo, Wanwan;Zhao, Mengkai;Cui, Zhihua;Xie, Liping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3565-3583
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    • 2022
  • The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

성능 향상을 위한 서버리스 컴퓨팅 동향과 발전 방향 (Survey on the Performance Enhancement in Serverless Computing: Current and Future Directions)

  • 이은영
    • 정보처리학회 논문지
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    • 제13권2호
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    • pp.60-75
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    • 2024
  • 클라우드 환경에서 복잡한 가상 환경을 관리할 필요 없이 애플리케이션 본연의 작업에 집중하기를 원하는 사용자의 요구는 서버리스 컴퓨팅이라는 새로운 컴퓨팅 모델을 탄생시켰다. 서버리스 컴퓨팅 모델에서 사용자는 서버에서의 자원 할당이나 기타 서버 관리를 서비스 제공자에게 위임하고, 자신은 애플리케이션 코드 개발에만 집중하여 클라우드 서비스를 사용하는 것이 가능해졌다. 서버리스 컴퓨팅은 클라우드 서비스 사용자의 부담을 감소시킴으로써 클라우드 컴퓨팅의 활용도를 한 단계 업그레이드시켰으며, 향후 클라우드 컴퓨팅의 기반 모델로 자리 잡을 것으로 예상된다. 서버리스 플랫폼은 사용자를 대신하여 클라우드 가상 환경에 대한 관리를 담당하며, 애플리케이션을 구성하는 서버리스 함수를 클라우드 환경에서 실행시키는 역할을 담당한다. 사용하는 자원에 비례하여 사용자 과금이 이루어지는 서버리스 컴퓨팅의 특징을 고려 할 때 서버리스 플랫폼의 효율성은 사용자와 서비스 제공자 모두에게 매우 중요한 요소라고 볼 수 있다. 본 논문에서는 서버리스 컴퓨팅 성능에 영향을 미치는 다양한 요소를 판별하고, 관련된 최신 연구 동향을 분석하고자 한다. 그리고 분석 결과를 바탕으로 향후 서버리스 컴퓨팅의 발전 방향과 관련된 연구 방향을 논의한다.

Design and evaluation of a GQS-based time-critical event dissemination for distributed clouds

  • Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • 제22권5호
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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.

Resource-efficient load-balancing framework for cloud data center networks

  • Kumar, Jitendra;Singh, Ashutosh Kumar;Mohan, Anand
    • ETRI Journal
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    • 제43권1호
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    • pp.53-63
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    • 2021
  • Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

Enhancing cloud computing security: A hybrid machine learning approach for detecting malicious nano-structures behavior

  • Xu Guo;T.T. Murmy
    • Advances in nano research
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    • 제15권6호
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    • pp.513-520
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    • 2023
  • The exponential proliferation of cutting-edge computing technologies has spurred organizations to outsource their data and computational needs. In the realm of cloud-based computing environments, ensuring robust security, encompassing principles such as confidentiality, availability, and integrity, stands as an overarching imperative. Elevating security measures beyond conventional strategies hinges on a profound comprehension of malware's multifaceted behavioral landscape. This paper presents an innovative paradigm aimed at empowering cloud service providers to adeptly model user behaviors. Our approach harnesses the power of a Particle Swarm Optimization-based Probabilistic Neural Network (PSO-PNN) for detection and recognition processes. Within the initial recognition module, user behaviors are translated into a comprehensible format, and the identification of malicious nano-structures behaviors is orchestrated through a multi-layer neural network. Leveraging the UNSW-NB15 dataset, we meticulously validate our approach, effectively characterizing diverse manifestations of malicious nano-structures behaviors exhibited by users. The experimental results unequivocally underscore the promise of our method in fortifying security monitoring and the discernment of malicious nano-structures behaviors.

공용 클라우드 기반 PC 실습실 서비스의 실시간 비용 예측 모델 연구 (A Study on Realtime Cost Estimation Model of PC Laboratory Service based on Public Cloud)

  • 조경운;신용현
    • 한국인터넷방송통신학회논문지
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    • 제19권3호
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    • pp.17-23
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    • 2019
  • IaaS는 인프라 하드웨어를 소유하지 않고 필요에 따라 임대하는 새로운 방식의 컴퓨팅 서비스로서 비용측면에서 매우 효율적인 것으로 알려져 있다. 일반적으로 사용량에 따른 과금 방식을 채택하므로 인프라 비용에 민감한 서비스를 운영하기에 적합하다. 이러한 서비스를 운영하는 책임자는 예상되는 소요 비용을 조기에 파악하여 클라우드 활용 정책을 적시에 변경하기를 원할 것이다. 그러나 클라우드 서비스 제공자들은 십수시간 지연된 과금 정보를 제공하여 신속한 대처가 불가능하다. 본 논문에서는 가상 머신 인스턴스 수준에서 사용량을 모니터링하고 이에 기반하여 실시간 IaaS 비용 예측 모델을 제안한다. 이 모델 검증을 위하여 1학기 동안의 공용 클라우드 기반의 PC 실습실 서비스를 운용하였으며, 이를 통하여 부과된 실제 금액과의 차이는 평균 5.2% 이하임을 확인하였다.

BCOR 접근법을 이용한 클라우드 컴퓨팅 도입의 의사결정 요인에 관한 연구 (A Study on Decision Making Factors of Cloud Computing Adoption Using BCOR Approach)

  • 이영찬;당응웬하인
    • 한국IT서비스학회지
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    • 제11권1호
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    • pp.155-171
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    • 2012
  • With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners' effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.