• 한국컴퓨터정보학회논문지
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• 제13권1호
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• pp.1-10
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• 2008

이 기종의 네트워크와 시스템 자원으로 구성된 그리드 컴퓨팅 환경에서 대용량 데이터를 빠르고 정확하게 처리하기 위해서는 효과적인 그리드 자원선택이 필수적이다. 이를 위해 본 논문은 의사결정 트리 기법을 이용한 그리드 자원선택 시스템을 제안한다. 이 시스템은 자원 정보를 기록한 데이터 셋을 바탕으로 사용자들이 선택하는 자원들을 처리 할 데이터의 특성과 사용자의 요구사항으로 분석해서 자원선택을 위한 의사결정 트리를 구축한다. 그리드 사용자의 자원 요청 시 의사결정 트리를 탐색하여 사용자 요구 및 작업 특성에 적합한 자원들을 선택하여 작업을 할당함으로써 사용자 만족도를 향상시킴은 물론 전체 그리드 시스템의 성능을 개선한다. 실험결과는 본 논문에서 제안한 의사결정 트리 기반의 그리드 자원선택 시스템이 기존 그리드 자원선택 시스템인 Condor-G 및 Nimrod-G와 비교하여 더 높은 작업 처리율 및 자원 이용률과 더 적은 작업 손실 및 처리시간을 제공함으로써 그리드 자원선택 및 데이터 분산 처리에 효과적이라는 사실을 증명한다

• Asian Journal of Innovation and Policy
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• 제13권1호
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• pp.57-67
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• 2024

This paper analyzes the factors influencing the selection of supercomputing resources. Using the results of a survey targeting supercomputing resources in the public sector, a resource selection model was presented through logistic regression and principal component analysis methods. As a result of the analysis, it was confirmed that affiliation, purpose of use, size of research funding, possession of a supercomputer, and whether specialized services are needed have a significant impact on resource selection. In the future, we expect that the results of this study will be used in various ways to manage demand for supercomputing resources.

• 한국전자거래학회지
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• 제17권1호
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• pp.53-74
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• 2012

본 연구에서는 비즈니스 프로세스 관리(Business Process Management, BPM) 환경에서 자원의 성능에 영향을 미치게 되는 여러 요소를 고려하여 인적자원을 선택하는 방법론을 개발한다. 스케줄링에 있어서 자원의 선택 문제는 작업 수행도에 직접적인 영향을 미치기 때문에 중요한 문제로 인식되어져 왔다. 비록 많은 문제에 있어서 전통적인 자원선택 방법론이 의미를 가져왔으나, 인적자원을 다루는데 있어서는 가장 좋은 방법론이라고 볼 수 없다. 인적자원은 작업부하, 작업소요시간, 작업간 시간 등의 다양한 요소에 의해서 영향을 받는 특이한 요소이며 본 연구는 이러한 다양한 요소를 고려하여 작업자를 선택하는 방법론을 제시한다. 이를 위해서 베이지안 네트워크를 사용하며, 앞서 기술한 여러 요소들을 한꺼번에 고려하기 위한 베이지안 선택규칙(Bayesian Selection Rule, BSR)을 도입하였다. 또한, 시뮬레이션을 통해서 본 연구에서 개발된 방법론이 대기시간, 작업수행시간과 사이클 타임을 줄일 수 있음을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.68-86
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• 2015

Future wireless network aims to integrate different radio access networks (RANs) to provide a seamless access and service continuity. In this paper, a new resource denotation method is proposed in the WLAN and LTE heterogeneous networks based on a concept of spectral bandwidth mapping. This method simplifies the denotation of system resources and makes it possible to calculate system residual capacity, upon which an economic model-based network selection algorithm is designed in both under-loaded and over-loaded scenarios in the heterogeneous networks. The simulation results show that this algorithm achieves better performance than the utility function-based access selection (UFAS) method proposed in [12] in increasing system capacity and system revenue, achieving load balancing and reducing the new call blocking probability in the heterogeneous networks.

• 한국경영과학회지
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• 제16권2호
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• pp.61-61
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• 1991

We propose a strategic R&D resource allocation and project selection model based on national R&D policy and objectives. First, contributions to R&D policy and objectives for each R&D area are evaluated by using analytical hierarchy process (AHP). Second, fuzzy Delphi are proposed to estimate R&D budget for each R&D area. Then, a project selection grid is also introduced to implement two-phased evaluation for R&D project selection. We also discuss how to improve the consistency in AHP and how to reduce the pairwise comparison in AHP. The proposed model enables the decision makers to allocate R&D budget, and to evaluate and select the R&D proposals based on both the contribution to national R&D policy and objectives, and the size of each R&D area concurrently

• 경영과학
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• 제16권2호
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• pp.61-77
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• 1999

We propose a strategic R&D resource allocation and project selection model based on national R&D policy and objectives. First, contributions to R&D policy and objectives for each R&D area are evaluated by using analytical hierarchy process (AHP). Second, fuzzy Delphi are proposed to estimate R&D budget for each R&D area. Then, a project selection grid is also introduced to implement two-phased evaluation for R&D project selection. We also discuss how to improve the consistency in AHP and how to reduce the pairwise comparison in AHP. The proposed model enables the decision makers to allocate R&D budget, and to evaluate and select the R&D proposals based on both the contribution to national R&D policy and objectives, and the size of each R&D area concurrently.

• Journal of Information Technology Applications and Management
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• 제15권1호
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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.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• ETRI Journal
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• 제34권3호
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• pp.341-351
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• 2012

We deal with a resource allocation problem for multimedia service discrimination in wireless networks. We assume that a service provider allocates network resources to users who can choose and access one of the discriminated services. To express the rational service selection of users, the utility function of users is devised to reflect both service quality and cost. Regarding the utility function of a service provider, total profit and efficiency of resource usage have been considered. The proposed service discrimination framework is composed of two game models. An outer model is a repeated Stackelberg game between a service provider and a user group, while an inner model is a service selection game among users, which is solved by adopting the Kalai-Smorodinsky bargaining solution. Through simulation experiments, we compare the proposed framework with existing resource allocation methods according to user cost sensitivity. The proposed framework performed better than existing frameworks in terms of total profit and fairness.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.