• ETRI Journal
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• v.43 no.1
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• pp.53-63
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• 2021

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

• Journal of the Korean Institute of Gas
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• v.19 no.1
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• pp.28-37
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• 2015

This study presents the development of a well placement optimization model, combining an artificial neural network, which enables high-speed calculation, with a simulated annealing algorithm. The conventional FDM simulator takes excessive time when used to perform a field scale reservoir simulation. In order to solve this problem, an artificial neural network was applied to the model to allow the simulation to be executed within a short time. Also by using the given result, the optimization method, SA algorithm, was implemented to automatically select the optimal location without taking any subjective experiences into consideration. By comparing the result of the developed model with the eclipse simulator, it was found that the prediction performance of the developed model has become favorable, and the speed of calculation performance has also been improved. Especially, the optimum value was estimated by performing a sensitivity analysis for the cooling rate and the initial temperature, which is the control parameter of SA algorithm. From this result, it was verified that the calculation performance has been improved, as well. Lastly, an optimization for the well placement was performed using the model, and it concluded the optimized place for the well by selecting regions with great productivity.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4640-4661
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• 2018

To cope with the explosive growth of Internet services, Service Function Chaining (SFC) based on Software-defined Networking (SDN) is an emerging and promising technology that has been suggested to meet this challenge. Determining the placement of Virtual Network Functions (VNFs) and routing paths that optimize the network utilization and resource consumption is a challenging problem, particularly without violating service level agreements (SLAs). This problem is called the optimal SFC placement problem and an Integer Linear Programming (ILP) formulation is provided. A greedy heuristic solution is also provided based on an improved two-step mapping algorithm. The obtained experimental results show that the proposed algorithm can automatically place VNFs at the optimal locations and find the optimal routing paths for each online request. This algorithm can increase the average request acceptance rate by about 17.6% and provide more than 20-fold reduction of the computational complexity compared to the Greedy algorithm. The feasibility of this approach is demonstrated via NetFPGA-10G prototype implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• Journal of KIBIM
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• v.10 no.3
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• pp.43-53
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• 2020

BIM-based Cloud platform gained popularity coupled with the convergence of Fourth Industrial Revolution technology. However, most of the previous work has not guaranteed sufficient efficiency to meet user requirements according to BIM service. Furthermore, the Cloud environment is only used as a server and it does not consider cloud characteristics. For the processing of High Capacity Data like BIM and using seamless BIM service, Resource management technology is required in the cloud environment. In this paper, to solve the problems, we propose a BIM platform for BaaS and an efficient resource allocation scheme. We also proved the efficiency of resource for the proposed scheme by using existing schemes. By doing this, the proposed scheme looks forward to accelerating the growth of the BaaS through improving the user experience and resource efficiency.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.640-652
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• 2020

This study identifies the statues of the resource development in residential facilities for people with disabilities to review the current level and propose necessary supporting measures to revitalize resource development in this current time when the importance of resource development is rising for social welfare organizations. Specifically, this study conducted a survey on the current statues and needs for resource development and focus group interviews to acquire in-depth opinions on the need for resource development and supporting measures in 255 nationwide residential facilities for the disabled. The results showed that 50% of the resource development for the residential facilities depended on private donations, while the presence of exclusive workforce made differences among development plans, performance and achievement. Also, their resource development methods were limited around direct requests, such as personal recommendations, as they are faced with challenges such as inadequate related expertise and technologies for resource development, lack of exclusive workforce, and lack of interest in available facilities in the local community. With reference to these findings, this study proposes the following development measures: placement of exclusive workforce, adoption of diverse resource development methods, transparent and reliable resource development, and preparation for systematic step-by-step professional training on resource development.

• Journal of Platform Technology
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• v.10 no.4
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• pp.70-81
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• 2022

In this paper, we proposed a Virtual Machine Placement (VMP) method to provide live vertical scaling services for cloud resources. Since free space on the physical server must be secured in advance for vertical scaling, a "general-mixed-vertical" mode conversion algorithm based on the FirstFit placement strategy that variably adjusts the allocation ratio of virtual servers to physical servers for this purpose is presented. Simulations were performed using parameters such as vertical scaling ratio, virtualization ratio, and free resource ratio. When the vertical scaling ratio is 50%, considering free space, 150% of resources are required as a whole, but simulation results of the proposed algorithm show that only up to 125% of free space is required.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.705-710
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• 2000

Recently, use of sea-sand as fine aggregates in reinforced concrete structures is increasing because of lacking of supply due to destructive of environment caused by obtaining and exhausting of resource. It rise up issue, some field reconstruction, interrupted construction works occurring to the trouble on the site because sometimes engineer does not agree to use of corroded bar, even slighly corroded. This study investigates the properties of bond strength and the structural behavior of corroded bars before and after placement. The purpose of the study is to present the database estimating degree of damaged bond strength according to corrosion level and deciding on whether using corroded bars or not.