• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1063-1075
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• 2022

In recent years, container techniques have been broadly applied to cloud computing systems to maximize their efficiency, flexibility, and economic feasibility. Concurrently, studies have also been conducted to ensure the security of cloud computing. Among these studies, moving-target defense techniques using the high agility and flexibility of cloud-computing systems are gaining attention. Moving-target defense (MTD) is a technique that prevents various security threats in advance by proactively changing the main attributes of the protected target to confuse the attacker. However, an analysis of existing MTD techniques revealed that, although they are capable of deceiving attackers, MTD techniques have practical limitations when applied to an actual cloud-computing system. These limitations include resource wastage, management complexity caused by additional function implementation and system introduction, and a potential increase in attack complexity. Accordingly, this paper proposes a software-defined MTD system that can flexibly apply and manage existing and future MTD techniques. The proposed software-defined MTD system is designed to correctly define a valid mutation range and cycle for each moving-target technique and monitor system-resource status in a software-defined manner. Consequently, the proposed method can flexibly reflect the requirements of each MTD technique without any additional hardware by using a software-defined approach. Moreover, the increased attack complexity can be resolved by applying multiple MTD techniques.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.59-66
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• 2024

This paper presents the concept and characteristics of cloud computing, and it addresses how cloud computing delivers quality of service (QoS) to the end-user. Next, it discusses how to schedule one's workload in the infrastructure using technologies that have recently emerged such as Machine Learning (ML). That is followed by an overview of how ML can be used for resource management. This paper then looks at the primary goal of this project, which is to outline the benefits of using ML to schedule upcoming demands to achieve QoS and conserve energy. In this survey, we reviewed the research related to ML methods for predicting workloads in cloud computing. It also provides information on the approaches to elasticity, while another section discusses the methods of prediction used in previous studies and those that used in this field. The paper concludes with a summary of the literature on predicting workloads and optimising QoS in the cloud computing.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.896-914
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• 2020

With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2649-2666
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• 2015

In the dynamic cloud computing environment, to ensure, under the terms of service-level agreements, the maximum efficiency of resource utilization, it is necessary to investigate the online dynamic management of virtual machine resources and their operational application systems/components. In this study, the feasibility and properties of the division of virtual machine resources on the cloud platform, using the virtual machine cluster as the management unit, are investigated. First, the definitions of virtual machine clusters are compared, and our own definitions are presented. Then, the feasibility of division using the virtual machine cluster as the management unit is described, and the isomorphism and reconfigurability of the clusters are proven. Lastly, from the perspectives of clustering and cluster segmentation, the dynamics of virtual machines are described and experimentally compared. This study aims to provide novel methods and approaches to the optimization management of virtual machine resources and the optimization configuration of the parameters of virtual machine resources and their application systems/components in large-scale cloud computing environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.391-396
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• 2021

In this study, items for forest policy and forest resource research in Austria, Japan, New Zealand, and Indonesia, which are major forest advanced countries, were investigated, and the applicability of point cloud data acquired through laser scanning was identified. Through the study, it was found that forest policies in developed countries are being pursued for the purpose of sustainable forest conservation and management, job creation, and timber productivity improvement, and that new technologies are being researched and applied to actual projects. Korea has a high proportion of forests compared to the national land area compared to major forestry developed countries, but the accumulation of trees is relatively low, so it is a time for scientific forest management to improve the accumulation of trees. To understand the applicability of laser scanning technology, a forest resource survey using point cloud data was conducted, and the diameter of breast height, height, number of trees per unit area were calculated, and the shape of the crown was identified. If field experiments and accuracy evaluations applying various laser scanning technologies are carried out in the future, it will be possible to present the quantitative improvement of forest resource survey using foil cloud.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.178-180
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• 2017

Virtualization was devised as a resource management and optimization technique for mainframes having scaleless computing capabilities. The resource scaling can be done with a variety of virtualization methods such as VM creation, deletion, and migration. In this paper, we designed to achieve the load balancing, several load balancing schemes such as Minimum Execution Time (MET), Min-Min scheduling, Cloud Analyst have been reported in literature in addition to a comprehensive study on First Come First Serve (FCFS) and Round-robin schedulers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.639-643
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• 2018

Laws concerning the protection of personal information have been enacted and revised as the legislation on personal information protection on the basis of the Act on the Protection of Personal Information Maintained by Public Institutions. Nevertheless, there have been continuing threats resulting from the fact that restrictions on security subject to laws remain unclear. By proposing protected access utilizing a unique identification key of enterprises, regarding the personal information of various internal and external clients held by international manufacturing companies and attempting to make policy aspect and management access at the same time, there is a change of gradual decline in cloud personnel information management service, which is the domestic ISP service for personnel management as the technology facilitated to reduce the burden on personnel and cost for the protection of personal information and the market is also changing to the direction for companies to directly operate. Therefore, this study intends to examine the convenience of integrated management for ensuring security, while confirming the gap on flexibility and safety on management point regarding the human resources of international manufacturing companies arising from its interactions.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.60-75
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• 2024

The demand of users, who want to focus on the core functionality of their applications without having to manage complex virtual environments in the cloud environment, has created a new computing model called serverless computing. Within the serverless paradigm, resource provisioning and server administration tasks are delegated to cloud services, facilitating application development exclusively focused on program logic. Serverless computing has upgraded the utilization of cloud computing by reducing the burden on cloud service users, and it is expected to become the basic model of cloud computing in the future. A serverless platform is responsible for managing the cloud virtual environment on behalf of users, and it is also responsible for executing serverless functions that compose applications in the cloud environment. Considering the characteristics of serverless computing in which users are billed in proportion to the resources used, the efficiency of the serverless platform is a very important factor for both users and service providers. This paper aims to identify various factors that affect the performance of serverless computing and analyze the latest research trends related to it. Drawing upon the analysis, the future directions for serverless computing that address key challenges and opportunities in serverless computing are proposed.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.77-83
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• 2010

Recently, IT-based environment is changing rapidly as changing in web services platform, evolution of cloud computing environments and expanding the base of a smart market. Accordingly, monitoring development of environment is changing quickly. So a customizable SaaS-based monitoring tool is required to provide monitoring services. It has to support a variety of environmental monitoring and a resource managers with requested information, and by an enhanced monitoring framework in clouding environment of management system. In this paper, the 3D viewer for the management of sensor node management system was designed and built. Through the 3D viewer by enhancing the accessibility and visibility, the sensor network will allow resources to be used efficiently.