• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.1-10
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• 2008

In order to high-performance data Processing, effective resource selection is needed since grid resources are composed of heterogeneous networks and OS systems in the grid environment. In this paper. we classify grid resources with data properties and user requirements for resource selection using a decision tree method. Our resource selection method can provide suitable resource selection methodology using classification with a decision tree to grid users. This paper evaluates our grid system performance with throughput. utilization, job loss, and average of turn-around time and shows experiment results of our resource selection model in comparison with those of existing resource selection models such as Condor-G and Nimrod-G. These experiment results showed that our resource selection model provides a vision of efficient grid resource selection methodology.

• 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.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.53-74
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• 2012

This study developed a method for selection of available human resources for incomingjob allocation that considers factors affecting resource performance in the business process management (BPM) environment. For many years, resource selection has been treated as a very important issue in scheduling due to its direct influence on the speed and quality of task accomplishment. Even though traditional resource selection can work well in many situations, it might not be the best choice when dealing with human resources. Humanresource performance is easily affected by several factors such as workload, queue, working hours, inter-arrival time, and others. The resource-selection rule developed in the present study considers factors that affect human resource performance. We used a Bayesian Network (BN) to incorporate those factors into a single model, which we have called the Bayesian Selection Rule (BSR). Our simulation results show that the BSR can reduce waiting time, completion time and cycle time.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.169-177
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• 2008

Grid resources are composed of various communication networks and operation systems. When a grid system searches and selects grid resources, which meet requirements of a grid user, existing grid resource selection systems are limited due to their storage methods for resource information. In order to select grid resources suitable for requirements of a grid user and characteristics of data, this paper constructs an ontology for grid resources and proposes an ontology-based grid resource selection system. This system provides an inference engine based on rules defined by SWRL to create a resource list. Experimental results comparing the proposed system with existing grid resource selection systems, such as the Condor-G and the Nimrod-G, verify the effectiveness of the ontology-based grid resource selection system with improved job throughput and resource utilization and reduced job loss and job processing time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1340-1346
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• 2022

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) using multiple transmit antennas, where the transmit antenna selection scheme is used to reduce the system complexity. Thus, in this paper, we propose radio resource allocation and receiver selection schemes in order to improve the outage probability performance of the downlink NOMA system using the transmit antenna selection scheme. In particular, the receiver selection scheme is a method of grouping the receivers to improve the outage probability performance, and the radio resource allocation scheme is a method of allocating radio resources to each group in order to enhance the outage probability performance. In addition, through the computer simulation under the assumption of independent Rayleigh fading channels, we show that the proposed radio resource allocation and receiver selection schemes can improve the outage probability performance at the expense of the sum rate performance.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.271-282
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• 2008

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method, comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1058-1068
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• 2017

In V2X communication, a random based resource selection scheme is needed with considerations of cases that support devices without sidelink reception capabilities and require reduction of UE's power consumption. In this paper, as improvement of D2D's resource section scheme that one TRP is repeated to data subframe pool within a PSCCH period, it is proposed that different TRPs is applied for enhanced random resource selection based on pseudo-random sequence having UE-specific seed value. By results of proposed scheme's performance by numerical analysis, it is confirmed that collision probability among resources allocated to each UE for data TB is reduced, and a number of UEs which can avoid resource collision as much as possible and have simultaneous resource allocation is increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3008-3028
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• 2022

In this paper, we investigate traffic scheduling for a delay-sensitive multi-hop relay network, and aim to minimize the priority-based end-to-end delay of different data packet via joint relay selection, subcarrier assignment, and power allocation. We first derive the priority-based end-to-end delay based on queueing theory, and then propose a two-step method to decompose the original optimization problem into two sub-problems. For the joint subcarrier assignment and power control problem, we utilize an efficient particle swarm optimization method to solve it. For the relay selection problem, we prove its convexity and use the standard Lagrange method to deal with it. The joint relay selection, subcarriers assignment and transmission power allocation problem for each hop can also be solved by an exhaustive search over a finite set defined by the relay sensor set and available subcarrier set. Simulation results show that both the proposed routing scheme and the resource allocation scheme can reduce the average end-to-end delay.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.404-413
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• 2008

The ultimate goal of human resource management is to improve the organization's performance. This study explored how human resource management practices such as recruitment and selection, training and development, compensation and benefits, and performance appraisal affect the organizational commitment of Korean hotel restaurants. The results of this study shows that recruitment and selection, training and development have influence on affective organizational commitment, while compensation and benefits, and performance appraisal have impact on continuance organizational commitment. These findings have significant implications in presenting a new directions for human resource management in the operation of hotel restaurant business.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.45-61
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• 2022

Despite of the consensus on the critical role of CEO and slack resources for strategic decision making, how they affect in the selection of strategic alliance type is limited. This study investigated the effect of CEO's experiential attributes and the venture firms' slack resource on the selection of strategic alliance type. To this end, this study used multi-variate logistic regression analysis with 1,813 Korean venture firms. The findings indicated that higher education level and large firm experience of CEO positively contributed to form an explorative alliance. And these two experiential attributes has negative effects on the probability of exploitative alliance formation. On the other hand, the entrepreneurial experience has no effect on the selection of strategic alliance type. This study also investigated the effect of slack resource - available slack, recoverable slack, and potential slack-. The more venture firms have available and potential slack, the higher probability of pursuing an explorative alliance. In addition, recoverable slack of venture firms has negative effect only on the selection of explorative alliance. The results of this study are expected to contribute the literatures of strategic management and venture firms by illustrating which CEO and firm-level factors affect the selection of strategic alliance type. This study also extends recent effort to better understand the selection of strategic alliance type with upper echelons theory and slack resource. And this study suggests implications that can increase the probability of successful decision making by venture firms in selection of strategic alliance type.