• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1544-1572
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• 2011

Task placement and scheduling are traditionally studied in following aspects: resource utilization, application throughput, application execution latency and starvation, and recently, the studies are more on application scalability and application performance. A methodology for task placement and scheduling centered on tasks based on virtual machines is studied in this paper to improve the performances of systems and dynamic adaptability in applications development and deployment oriented parallel computing. For parallel applications with no real-time constraints, we describe a thought of feature model and make a formal description for four layers of task placement and scheduling. To place the tasks to different layers of virtual computing systems, we take the performances of four layers as the goal function in the model of task placement and scheduling. Furthermore, we take the personal preference, the application scalability for a designer in his (her) development and deployment, as the constraint of this model. The workflow of task placement and scheduling based on virtual machines has been discussed. Then, an algorithm TPVM is designed to work out the optimal scheme of the model, and an algorithm TEVM completes the execution of tasks in four layers. The experiments have been performed to validate the effectiveness of time estimated method and the feasibility and rationality of algorithms. It is seen from the experiments that our algorithms are better than other four algorithms in performance. The results show that the methodology presented in this paper has guiding significance to improve the efficiency of virtual computing systems.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.103-111
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• 2016

Offloading tasks from mobile devices to available cloud servers were improved since the introduction of the cloudlet. With the implementation of dynamic offloading algorithms, mobile devices can choose the appropriate server for the set of tasks. However, current task distribution approaches do not consider the number of VM, which can be a critical factor in the decision making. This paper proposes a dynamic task distribution on clustered data centers. A proportional VM migration approach is also proposed, where it migrates virtual machines to the cloud servers proportionally according to their allocated CPU, in order to prevent overloading of resources in servers. Moreover, we included the resource capacity of each data center in terms of the maximum CPU in order to improve the migration approach in cloud servers. Simulation results show that the proposed mechanism for task distribution greatly improves the overall performance of the system.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.587-595
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• 2015

Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of central processing unit (CPU) cores. In order to support such large-scale scientific workflows, large-capacity cluster systems such as supercomputers are widely used. However, as users require a diversity of software packages and configurations, a system administrator has some trouble in making a service environment in real time. In this paper, we present a container-based cluster management platform and introduce an implementation case to minimize performance reduction and dynamically provide a distributed computing environment desired by users. This paper offers the following contributions. First, a container-based virtualization technology is assimilated with a resource and job management system to expand applicability to support large-scale scientific workflows. Second, an implementation case in which docker and HTCondor are interlocked is introduced. Lastly, docker and native performance comparison results using two widely known benchmark tools and Monte-Carlo simulation implemented using various programming languages are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.143-150
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• 2019

Cloud computing has recently become an attractive solution for massively multiplayer online games(MMOGs), as it lifts operators from the burden of buying and maintaining hardware. Peer-to-peer(P2P) -based solutions present several advantages, including the inherent scalability, self-repairing, and natural load distribution capabilities. We propose a hybrid architecture for MMOGs that combines technological advantages of two different paradigms, P2P and cloud computing. An efficient and effective provisioning of resources and mapping of load are mandatory to realize an architecture that scales in economical cost and quality of service to large communities of users. As the number of simultaneous players keeps growing, the hybrid architecture relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. For MMOGs, besides server time, bandwidth costs represent a major expense when renting on-demand resources. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed hybrid architecture can reduce the bandwidth at the server while utilizing enough bandwidth of players.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.1
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• pp.155-167
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• 2012

Cloud computing service is a next generation IT service which has pay-per-use billing model and supports elastically provisioning IT infra according to user demand. However it has many potential threats originating from outsourcing/supporting service structure that customers 'outsource' their own data and provider 'supports' infra, platform, application services, the complexity of applied technology, resource sharing and compliance with a law, etc. In activation of Cloud service, we need objective assessment standard to ensure safety and reliability which is one of the biggest obstacles to adopt cloud service. So far information security management system has been used as a security standard for a security management and IT operation within an organization. As for Cloud computing service it needs new security management and assessment different from those of the existing in-house IT environment. In this paper, to make a Information Security Management System considering cloud characteristics key components from threat management system are drawn and all control domain of existing information security management system as a control components are included. Especially we designed service security management to support service usage in an on-line self service environment and service contract and business status.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.63-72
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• 2013

Cloud services is recognized the essential IT infrastructure in the optimal smart society which is changing rapidly as a low-cost and high-efficiency. This service of starting from prominent overseas companies such as Google, Amazon, had influenced on the introduction of the service for the various policies of foreign governments, including the United States and the United Kingdom. Such countries adopt to the cloud computing and make transform to the cloud service of existing public service for the effective management of information resources. In this study, we propose a model for adoption of appropriate cloud-based public services in Korea through analyzing the foreign government case of adoption of cloud services.

• Journal of the Korea Convergence Society
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• v.7 no.1
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• pp.1-8
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• 2016

Cloud computing technology offers function that share each other computer resource, software and infra structure based on network. Virtualization is a very useful technology for operation efficiency of enterprise's server and reducing cost, but it can be target of new security threat when it is used without considering security. This paper proposes access control mechanism based on MAC(Mandatory Access Control) for cloud convergence that solve various problem that can occur in cloud environment. This mechanism is composed of set of state rules, security characteristics and algorithm. Also, we prove that the machine system with access control mechanism and an initial secure state is a secure system. This policy module of mechanism is expected to not only provide the maintenance but also provide secure resource sharing between virtual machines.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.37-47
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• 2011

Current researches in the Cloud focus on the appropriate interactions of cloud components in a large-scale system implementation. However, the current designs do not include intelligent methods like grouping the similar service providers based on their properties and integrating adaptive schemes for load distribution which can promote effective sharing of resource. This paper proposes an efficient virtualization of services by grouping the cloud providers to improve the service provisioning. The grouping of cloud service providers based on a cluster analysis collects the similar and related services in one group. The adaptive load balancing supports the service provisioning of the cloud system where it manages the load distribution within the group using an adaptive scheme. The proposed virtualization mechanism (GRALB) showed good results in minimizing message overhead and throughput performance compared to other methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.69-78
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• 2015

Recently, due to the development of next-generation computing devices and high-performance network, VDI (Virtual Desktop Infrastructure) is receiving a great deal of attention from IT market as an essential part of cloud computing. VDI enables to host multiple, individual virtual machines that are provisioned from servers located at the data center by using hypervisor. One of the critical issues related to VDI is to reduce the performance difference between virtual machines and physical ones. In this paper, we present a real-time VM monitoring system, called SETMOV, that is able to collect the real-time resource usage information. We also present the performance results using iozone to verify SETMOV.