• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.84.2-84
• /
• 2001

To remove the logical error inexpensively, in this paper, we propose new concept of VPLF(Virtual PLC Framework) which consists of VPLE(Virtual PLC Editor), Virtual Machine(Virtual Machine), VMC(Virtual Machine Control panel), Virtual PLC Program Editor(VPLPE) and Object Inspector. VPLC is for PLC hardware and software and VM is for the target to be controlled. VPLC has an individual editor and the screen of configuration. With using individual editor in VPLC, we can edit and compile to PLC ladder program. In VM, there are many kinds of object for machine elements, actuator, sensor and so on. The VPLC and VM are interlinked each other and controlled by the PLC program in real time. So, we can get the powerful realization as the machine is ...

• KNOM Review
• /
• v.24 no.1
• /
• pp.1-12
• /
• 2021

VM (Virtual Machine) live migration is a server virtualization technique for deploying a running VM to another server node while minimizing downtime of a service the VM provides. Currently, in cloud data centers, VM live migration is widely used to apply load balancing on CPU workload and network traffic, to reduce electricity consumption by consolidating active VMs into specific location groups of servers, and to provide uninterrupted service during the maintenance of hardware and software update on servers. It is critical to use VMlive migration as a prevention or mitigation measure for possible failure when its indications are detected or predicted. In this paper, we propose two VNF live migration methods; one for predictive load balancing and the other for a proactive measure in failure. Both need machine learning models that learn periodic monitoring data of resource usage and logs from servers and VMs/VNFs. We apply the second method to a vEPC (Virtual Evolved Pakcet Core) failure scenario to provide a detailed case study.

• Journal of Information Processing Systems
• /
• v.9 no.3
• /
• pp.379-394
• /
• 2013

Cloud computing is an evolving computing paradigm that has influenced every other entity in the globalized industry, whether it is in the public sector or the private sector. Considering the growing importance of cloud, finding new ways to improve cloud services is an area of concern and research focus. The limitation of the available Virtual Machine Load balancing policies for cloud is that they do not save the state of the previous allocation of a virtual machine to a request from a Userbase and the algorithm requires execution each time a new request for Virtual Machine allocation is received from the Userbase. This problem can be resolved by developing an efficient virtual machine load balancing algorithm for the cloud and by doing a comparative analysis of the proposed algorithm with the existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.4
• /
• pp.1501-1518
• /
• 2016

This paper presents an effective management of VM (Virtual Machine) for heterogeneous cloud using Common Deployment Model (CDM) brokering mechanism. The effective utilization of VM is achieved by means of task scheduling with VM placement technique. The placements of VM for the physical machine are analyzed with respect to execution time of the task. The idle time of the VMis utilized productively in order to improve the performance. The VMs are also scheduled to maintain the state of the current VM after the task completion. CDM based algorithm maintains two directories namely Active Directory (AD) and Passive Directory (PD). These directories maintain VM with proper configuration mapping of the physical machines to perform two operations namely VM migration and VM roll back. VM migration operation is performed from AD to PD whereas VM roll back operation is performed from PD to AD. The main objectives of the proposed algorithm is to manage the VM's idle time effectively and to maximize the utilization of resources at the data center. The VM placement and VM scheduling algorithms are analyzed in various dimensions of the cloud and the results are compared with iCanCloud model.

• Journal of Information Processing Systems
• /
• v.13 no.3
• /
• pp.476-490
• /
• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.9
• /
• pp.965-972
• /
• 2004

This Paper presents the experiences of the static and dynamic library function connection technique for the embedded virtual machines, base on the native function connection methods of the virtual machines such as KVM, Waba VM. For this goals, we implements the new native function table for the static and dynamic library function connection technique base on the native function connection methods of the virtual machines such as KVM, Waba VM. And we presents the variety experiment and analysis results using the implemented technique.

• Journal of Energy Engineering
• /
• v.13 no.3
• /
• pp.199-204
• /
• 2004

This Paper deals with a Platform for diagnosis monitoring of DC-DC converter system based on Java virtual machine. This platform is designed for estimating diagnostic parameters of DC-DC converter system based on system identification method and displaying Web-page on operating status. For Web-service, hardware of platform is baled on a Strongarm processor and software bale is designed on Linux and java virtual machine.

• Journal of Internet Computing and Services
• /
• v.25 no.4
• /
• pp.39-46
• /
• 2024

An API gateway is a high-availability component that provides a single entry point for API clients outside the cloud to connect with services inside the cloud. It has a high risk of creating bottlenecks and requires redeployment when services change. The Java language, in which several API gateways are implemented, announced technologies called GraalVM Native Image and Virtual Thread to overcome problems with deployment and operational performance. Applying these technologies to Java applications requires changes to the source code and deployment procedures. In this study, the performance of the API gateway was measured and analyzed when it operated based on GraalVM Native Image and Java Virtual Machine(JVM) and between Virtual Thread and Reactive thread processing methods. In this study, evaluation indicators were selected to evaluate deployment performance and operational performance, and the performance of the evaluation indicators was measured and evaluated in four environments.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.60-66
• /
• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.