• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.513-525
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• 2013

Purpose: The purpose of this paper are to propose a strategic map for hotel industry through analyzing the relationship between service resource, operational capabilities, and performance. Methods: A phone survey was conducted among Korean hotels, and 102 data sets were collected. Measurement items are assessed using both cognitive and objective scales. Results: As results, 'superior group', which is superior in both physical resources and human resources, is excellent in all capabilities and also in room occupancy rate. On the other hands, 'inferior group', which is inferior in both physical resources and human resources, shows lower achievements is in most areas except speed. In addition, physical superior group is better than human superior group in most capabilities except speed, but human superior group shows better results than physical superior group in both room occupancy rate and customer satisfaction. Conclusions: Through the empirical analysis, the conclusions attained are as follows; First, human resources affect customer satisfaction more directly that physical resources. Second, the balancing between physical resources and human resources has an importance to improve operational capabilities.

• Nuclear Engineering and Technology
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• v.41 no.5
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• pp.747-752
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• 2009

A vulnerability assessment is essential for the efficient operation of a physical protection system (PPS). Previous assessment codes have used a simple model called an adversary sequence diagram. In this study, the use of a two-dimensional (2D) map of a facility as a model for a PPS is suggested as an alternative approach. The analysis of a 2D model, however, consumes a lot of time. Accordingly, a generalized heuristic algorithm has been applied to address this issue. The proposed assessment method was implemented to a computer code; Systematic Analysis of physical Protection Effectiveness (SAPE). This code was applied to a variety of facilities and evaluated for feasibility by applying it to various facilities. To help upgrade a PPS, a sensitivity analysis of all protection elements along a chosen path is proposed. SAPE will help to accurately and intuitively assess a PPS.

• Journal of the Korea Society for Simulation
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• v.21 no.2
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• pp.59-67
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• 2012

A grid computing consists of the physical resources for processing one of the large-scale jobs. However, due to the recent trends of rapid growing data, the grid computing needs a parallel processing method to process the job. In general, each physical resource divides a requested large-scale task. And a processing time of the task varies with an efficiency and a distance of each resource. Even if some resource completes a job, the resource is standing by until every divided job is finished. When every resource finishes a processing, each resource starts a next job. Therefore, this paper proposes a dynamic resource reallocation scheduling model (DDRSM). DDRSM finds a waiting resource and reallocates an unfinished job with an efficiency and a distance of the resource. DDRSM is an efficient method for processing multiple large-scale jobs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3841-3861
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• 2017

Virtualized small cell network is a promising architecture which can realize efficient utilization of the network resource. However, conventional full duplex self-backhauls lead to residual self-interference, which limits the network performance. To handle this issue, this paper proposes a virtual resource allocation, in which the residual self-interference is fully exploited by employing a physical-layer network coding (PNC) aided self-backhaul scheme. We formulate the features of PNC as time slot and information rate constraints, and based on that, the virtual resource allocation is formulated as a mixed combinatorial optimization problem. To solve the problem efficiently, it is decomposed into two sub problems, and a two-phase iteration algorithm is developed accordingly. In the algorithm, the first sub problem is approximated and transferred into a convex problem by utilizing the upper bound of the PNC rate constraint. On the basis of that, the convexity of the second sub problem is also proved. Simulation results show the advantages of the proposed scheme over conventional solution in both the profits of self-backhauls and utility of the network resource.

• Korean Journal of Social Welfare
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• v.65 no.2
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• pp.335-356
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• 2013

Physical resources are central to coping with economic hardships for people in low-income, yet life experiences such as resource loss and gain and their relationships with a sense of well-being received scarce attention. Thus this study investigated levels of loss and gain of physical resources, economic stability and well-being of 254 adults who participated in welfare-to-work programs; correlations and paths among these variables; and direct and indirect effects of economic stability by structural equation modeling. Major results were: first, the levels of resource loss and gain were below a moderate level and the level of gain was significantly higher than the loss level. Second, in the relationships with both economic stability and well-being, resource loss showed negative correlations, while resource gain showed significantly positive correlations. Third, the negative direct effect of resource loss either on the economic stability or on the well-being respectively was significant and the indirect effect on well-being through economic stability was also significant. Finally, the direct effect of resource gain on either economic stability or well-being was significant; and the indirect effect of resource gain on well-being was also significant. Thus in both models for resource loss and gain, the indirect effect of economic stability was significant, which supports partial mediation model. Based on these results, implications for social work practice and research were examined, particularly for enabling social work practice to utilize information regarding resource loss and gain, economic stability, and a sense of well-being that were embedded in the community life of people in low-income.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• Journal of Society of Preventive Korean Medicine
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• v.14 no.2
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• pp.57-66
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• 2010

Backgrounds : Since December 1, 2009, National Health Insurance began to reimburse for three physical therapies of Korean medicine. The extension of insurance coverage is demanded by Korean medicine societies. Objectives : This study aimed to measure the resource-based relative value scale (RBRVS) scores for thirty four physical therapies of Korean medicine and to estimate the insurer's expenditure for them in National Health Insurance. Methods : To measure the physician's work and the practice expense, the 'magnitude estimation method (MEM)' and the 'fully distributed cost - attributable cost method (FDC-ACM)' were applied respectively. We collected the frequency data of physical therapies from Korean medicine hospitals and clinics to estimate the total expenditure. Results : The resource-based relative value scale scores of physical therapies were measured from 23.44 to 160.66. Total insurer's expenditure was calculated to be 95.5 billion won as of 2009. Conclusions : Based on the result that showed minor increase of total expenditure, most physical therapies of Korean medicine need to be reimbursed in the National Health Insurance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.819-837
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• 2014

Data centers, which implement cloud service, have been faced up with quick growth of energy consumption and low efficiency of energy. 60GHz wireless communication technology, as a new option to data centers, can provide feasible approach to alleviate the problems. Aiming at energy optimization in 60GHz wireless data centers (WDCs), we investigate virtualization technology to assign virtual resources to minimum number of servers, and turn off other servers or adjust them to the state of low power. By comprehensive analysis of wireless data centers, we model virtual network and physical network in WDCs firstly, and propose Virtual Resource Mapping Packing Algorithm (VRMPA) to solve energy management problems. According to VRMPA, we adopt packing algorithm and sort physical resource only once, which improves efficiency of virtual resource allocation. Simulation results show that, under the condition of guaranteeing network load, VPMPA algorithm can achieve better virtual request acceptance rate and higher utilization rate of energy consumption.

• 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.