• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.193-199
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• 2012

Virtualization allows multiple commodity operating systems to share on a single physical machine. Resource allocation among virtual machines is a key to determine virtual machine performance. To satisfy time-sensitive task on a domain, hypervisor needs to observe the resource requirements and allocates proper amount of CPU resources in a timely manner. In this paper, we propose a realtime credit scheduler for latency sensitive application on virtual machines. The key idea is to register a time event in the Xen hypervisor. Experiment result shows that the proposed scheme is superior to Credit scheduler.

• Smart Media Journal
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• v.5 no.4
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• pp.18-25
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• 2016

Virtualized hardware resources provides efficiency in use and easy of management. Based on the benefits, virtualization techniques are used to build large server clusters and cloud systems. The performance of a virtualized system is significantly affected by the virtual machine scheduler. However, the existing virtual machine scheduler have a problem in that the I/O response is reduced in accordance with the scheduling delay becomes longer. In this paper, we introduce the Loan/Redemption mechanism of a virtual machine scheduler in order to improve the responsiveness to I/O events. The proposed scheme gives additional credits for to virtual machines and classifies the task characteristics of each virtual machine by analyzing the credit consumption pattern. When an I/O event arrives, the scheduling priority of a virtual machine is temporally increased based on the analysis. The evaluation based on the implementation shows that the proposed scheme improves the I/O response 60% and bandwidth of virtual machines 62% compared to those of the existing virtual machine scheduler.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.13-18
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• 2015

Computational science simulations have been used to enable discovery in a broad spectrum of application areas, these simulations show irregular demanding characteristics of computing resources from time to time. The adoption of virtualized high performance cloud, rather than CPU-centric computing platform (such as supercomputers), is gaining interest of interests mainly due to its ease-of-use, multi-tenancy and flexibility. Basically, provisioning a virtual cluster, which consists of a lot of virtual machines, in a real-time has a critical impact on the successful deployment of the virtualized HPC clouds for computational science simulations. However, the cost of concurrently creating many virtual machines in constructing a virtual cluster can be as much as two orders of magnitude worse than expected. One of the main factors in this bottleneck is the time spent to create the virtual images for the virtual machines. In this paper, we propose a novel technique to minimize the creation time of virtual machine images and improve I/O performance of the provisioned virtual clusters. We also confirm that our proposed technique outperforms the conventional ones using various sets of experiments.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.51-59
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• 2017

With the growth of Cloud computing, it is important to consider resource management techniques to minimize the overall costs of management. In cloud environments, each host's utilization and virtual machine's request based on user preferences are dynamic in nature. To solve this problem, efficient allocation method of virtual machines to hosts where the classification of virtual machines and hosts is undetermined should be studied. In reducing the number of active hosts to reduce energy consumption, thresholds can be implemented to migrate VMs to other hosts. By using Fuzzy logic in classifying resource requests of virtual machines and resource utilization of hosts, we proposed an adaptive VM allocation and migration approach. The allocation strategy classifies the VMs according to their resource request, then assigns it to the host with the lowest resource utilization. In migrating VMs from overutilized hosts, the resource utilization of each host was used to create an upper threshold. In selecting candidate VMs for migration, virtual machines that contributed to the high resource utilization in the host were chosen to be migrated. We evaluated our work through simulations and results show that our approach was significantly better compared to other VM allocation and Migration strategies.

• ETRI Journal
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• v.36 no.5
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.12
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• pp.568-575
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• 2008

Server consolidation by sever virtualization can make one physical machine(PM) to run several virtual machines simultaneously. Although It is attractive in cost, it has complex workload behaviors. For that reason, efficient resource management method is required. Dynamic relocation of virtual machine(VM)[3,4] by live migration[1,2] is one of resource management methods. We proposed SCOA(Server Consolidation Optimizing Algorithm) : a fine-grained load balancing mechanism worked on this dynamic relocation mechanism. We could obtain accurate resource distribution information through pointed physical machines on multi dimensional resource usage coordination, so we could maintain more balanced resource state. In this paper, we show the effectiveness of our algorithm by comparison of experimental results between SCOA and sandpiper[3] by software simulation.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.1-8
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• 2017

In this paper, we propose a fault tolerance technique which enables embedded systems to run without interruption while its operating system and tasks fail. In order to improve reliability, the proposed scheme makes an embedded system run as a virtual machine on virtual machine monitor. It also prepares a contingency virtual machine at which periodical backups of the embedded system are saved. When an error occurs in the main virtual machine, the corresponding standby virtual machine takes a role of the main virtual machine and continues its operation. Especially such backups and switches of virtual machines are performed with minor performance degradation by manipulating page table entries in virtual machine monitor. By conducting performance evaluation studies, we show that the proposed scheme makes embedded system robust against errors while it does not degrade the performance of the system significantly.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.246-255
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• 2010

There exist virtual machine scheduling delays in virtualized environment in which virtual machines share physical resources. Many resource management systems have been proposed to provide better application QoS through monitoring and analyzing application performance and resource utilization of virtual machines. However, those management systems don't consider virtual machine scheduling delays, result in incorrect application performance evaluation and QoS violations In this paper, we propose an application behavior analysis considering the scheduling delays, and a virtual machine priority allocation scheme based on the analysis to improve the application response time by minimizing the overall virtual machine scheduling delays.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1432-1440
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• 2022

Recently, as Virtual Desktop Infrastructure(VDI) is widely used not only in office work environments but also in workloads that use high-spec multi-core-based applications, the requirements for real-time and stability of VDI are increasing. Accordingly, the display protocol used for remote access in VDI and performance optimization of virtual machines have also become more important. In this paper, we propose two ways to configure desktop virtualization for multi-core-based application operation. First, we propose a codec configuration of a display protocol with optimal performance in a high load situation due to multi-processing. Second, we propose a virtual CPU scheduling optimization method to reduce scheduling delay in case of CPU contention between virtual machines. As a result of the test, it was confirmed that the H.264 codec of Blast Extreme showed the best and stable frame, and the scheduling performance of the virtual CPU was improved through scheduling optimization.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.147-160
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• 2010

The system virtualization shows interest in the consolidation of servers for the efficient utilization of system resources. There are many various researches to utilize a server machine more efficiently through the system virtualization technique, and improve performance of the virtualization software. These researches have studied with the activity to control the resource allocation of virtual machines dynamically focused on CPU, or to manage resources in the cross-machine using the migration. However, the researches of the memory management have been wholly lacking. In this respect, the use of memory is limited to allocate the memory statically to virtual machine in server consolidation. Unfortunately, the static allocation of the memory causes a great quantity of the idle memory and decreases the memory utilization. The underutilization of the memory makes other side effects such as the load of other system resources or the performance degradation of services in virtual machines. In this paper, we suggest the dynamic allocation of the memory in Xen to control the memory allocation of virtual machines for the utilization without the performance degradation. Using AR model for the prediction of the memory usage and ACO (Ant Colony Optimization) algorithm for optimizing the memory utilization, the system operates more virtual machines without the performance degradation of servers. Accordingly, we have obtained 1.4 times better utilization than the static allocation.