• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.1-10
• /
• 2023

The Multi-access Edge Computing (MEC) paradigm equips network edge telecommunication infrastructure with cloud computing resources. It seeks to transform the edge into an IT services platform for hosting resource-intensive and delay-stringent services for mobile users, thereby significantly enhancing perceived service quality of experience. However, erratic user mobility impedes seamless service continuity as well as satisfying delay-stringent service requirements, especially as users roam farther away from the serving MEC resource, which deteriorates quality of experience. This work proposes a deep reinforcement learning based service mobility management approach for ensuring seamless migration of service instances along user mobility. The proposed approach focuses on the problem of selecting the optimal MEC resource to host services for high mobility users, thereby reducing service migration rejection rate and enhancing service availability. Efficacy of the proposed approach is confirmed through simulation experiments, where results show that on average, the proposed scheme reduces service delay by 8%, task computing time by 36%, and migration rejection rate by more than 90%, when comparing to a baseline scheme.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.7
• /
• pp.11-21
• /
• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.

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

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2012.01a
• /
• pp.5-6
• /
• 2012

본 논문에서는 가상머신에서 수행되는 어플리케이션의 서비스 품질을 보장하고, 클라우드 클러스터의 운영비용을 절감시킬 수 있는 자원 할당 감축기법을 제안한다. 이 기법은 가상머신의 자원 사용량 변화 추세를 분석하고 이를 토대로 확률적인 접근을 사용하여 새로운 자원 할당 감축량을 결정한다. 가상머신의 자원 사용량이 할당량을 초과하면 가상머신의 이주가 필요하다. 이때 발생하는 다운타임동안 가상머신의 어플리케이션은 서비스를 수행할 수 없기 때문에 클라우드 시스템의 성능이 저하된다. 따라서 성능평가에서는 가상머신의 자원 사용량이 할당량을 초과하는 횟수를 측정하여 Greedy 기법과 비교 평가함으로써 제안한 기법이 자원 할당 감축에 우수함을 검증한다.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.11
• /
• pp.1-7
• /
• 2014

In this paper, we propose a virtual machine(VM) remapping scheme that reduces VM relocation time on a cloud cluster. The proposed scheme finds VMs that should be migrated in sequence from a given VM map, and exchanges destinations of some VMs among them to reduce the VM relocation time. The VMs, the destinations of which will be exchanged, are chosen based on the amount of physical machine's available resources and migration completion time. The exchange of destinations is repeated until the VM relocation time cannot be shortened any further. Through a simulation, we show that the proposed scheme reduces VM relocation time by 42.7% in maximum.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.595-596
• /
• 2023

본 논문에서는 컨테이너 오케스트레이션 플랫폼에 대하여 분석하고자 한다. 공공 클라우드 전환 로드맵 검토에 따라 클라우드 네이티브 전환을 위한 기술로 컨테이너, 마이크로서비스, 컨테이너 오케스트레이션의 중요성이 강조되고 있다. 대표적인 컨테이너 오케스트레이션 도구인 Kubernetes, Docker Swarm, Mesos를 비교하며, 이들의 초기 설치 용이성, 볼륨 관리, 애플리케이션 배포, 장애 관리 등에 대해 분석하고, 이를 통해 각 도구의 장단점과 적용 상황에 따른 고려사항을 파악함으로써, 클라우드 네이티브 전환 로드맵 수립에 도움을 제공하고자 한다.

• Journal of information and communication convergence engineering
• /
• v.10 no.1
• /
• pp.61-65
• /
• 2012

Many public organizations have been adopting and operating various servers. These servers run on Windows, Unix, and Linux operating systems that generally use less than 10% of their capacity. For migrating a public organization to cloud computing, we must first virtualize the server environment. This article proposes a strategy for server virtualization that the National IT Industry Promotion Agency (NIPA) has done and describes the effects of a public organization migrating to cloud computing. The NIPA Computer Center planned an effective virtualization migration on various servers. This project of virtualization migration was conducted with the existing policy of separate x86 servers and Unix servers. There are three popular approaches to server virtualization: a virtual machine model, a paravirtual machine model, and virtualization at the operating system layer. We selected a VMware solution that uses the virtual machine model. We selected servers for virtualization in the following manner. Servers were chosen that had the highest rate of service usage and CPU usage and had been operating for five years or more. However, we excluded servers that require 80% or greater rates of CPU usage. After adopting the server virtualization technique, we consolidated 32 servers into 3 servers. Virtualization is a technology that can provide benefits in these areas: server consolidation and optimization, infrastructure cost reduction and improved operational flexibility, and implementation of a dual computing environment.

• Smart Media Journal
• /
• v.12 no.2
• /
• pp.66-75
• /
• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.215-218
• /
• 2012

스팟 인스턴스(Spot instance)는 클라우드 환경에서 사용자가 제시한 입찰 가격으로 클라우드 내의 자원을 이용하여 작업을 수행할 수 있게 하는 새로운 방식이다. 사용자는 자신의 입찰 금액이 클라우드 내의 스팟 인스턴스 가격을 초과하는 한 인스턴스를 실행할 수 있다. 그러나 입찰 가격이 스팟 가격보다 낮다면 작업 실패가 발생하고, 이로 인해 작업 완료 시간은 지연되며 서비스 품질은 저하된다. 이 문제를 해결하기 위해, 본 논문에서는 스팟 인스턴스에서 사용자 비드가 초과되어 작업 수행이 중지된 VM에 대하여 체크포인트 기법과 VM 이주(migration) 기법을 이용함으로써 작업 대기 시간을 줄이는 방법을 제안한다. 이는 작업 중인 스팟 인스턴스에서 작업 실패가 발생할 경우 다른 인스턴스로 이주하여 작업을 재수행하는 기법이다. 실험 결과는 제안하는 VM 이주 기법이 작업을 수행할 수 있는 스팟 인스턴스의 가용성을 증가시킬 수 있음을 보여준다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37B no.9
• /
• pp.806-813
• /
• 2012

In a cloud computing environment, various solutions were introduced to provide the service to users such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Desktop as a Service (DaaS). Nowadays, Mobile as a Service (MaaS) to provide the mobility in a cloud environment. In other words, users must have access to data and applications even when they are moving. Thus, to support the mobility to a mobile Thin-Client is the key factor. Related works to support the mobility for mobile devices were Mobile IPv6 and Proxy Mobile IPv6 which showed performance drawbacks such as packet loss during hand-over which could be very critical when collaborating with cloud computing environment. The proposed model in this paper deploys middleware and replica servers to support the data transmission among cloud and PMIPv6 domain. It supports efficient mobility during high-speed movement as well as high-density of mobile nodes in local mobility anchor. In this paper, through performance evaluation, the proposed scheme shows the cost comparison between previous PMIPv6 and verifies its significant efficiency.