• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3865-3883
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• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• 한국정보시스템학회지:정보시스템연구
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• 제23권4호
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• pp.75-91
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• 2014

The effective supply chain management(SCM) is a matter of survival in many firms because successful supply chains will effectively coordinate their processes, focus on delivering customer value, eliminate unnecessary costs in key functional areas, and create performance measurement systems. The balanced scorecard(BSC) is widely used to measure the performance of the SCM. The BSC framework suggests that balance is obtained by adopting performance measures from four different areas. In this study, we analyzed the causal relationship of SCM performance based on BSC framework. First, we reviewed the nested causal relationships among four different perspective of the BSC, namely, business process perspective, customer perspective, financial perspective, and innovation and learning perspective. Then, we used the chi-square difference test to identify the best model to fit the causal relationship of SCM performance. Of the 800 questionnaires posted, a total of 265 questionnaires were returned after one follow-up. A total of 66 questionnaires were eliminated due to largely missing values. The major finding says alternative model 3 is dominant to other models to fit causal relationships among four different perspective of the BSC. Innovation and learning perspective positively influence on customer perspective, business process perspective, and financial perspective. Business process perspective also positively influence on customer perspective and financial perspective whereas customer perspective does not influence on financial perspective significantly.

• ETRI Journal
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• 제42권5호
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• 산업경영시스템학회지
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• 제33권1호
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• pp.80-90
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• 2010

Performance management is very popular in business area and seems to be an exciting topic. Despite significant research efforts and myriads of performance metrics, performance management today as a rigorous approach is still in an immature state and metrics are often selected based on intuitive and heuristic approach. In a R&D sector, the difficulty to select the proper performance metrics is even more increasing due to the natural characteristics of R&D such as unique or domain-specific problems. In this paper, we present a way of presenting R&D performance framework using ontology language. Based on this, the specific metrics can be derived by reusing or inheriting the context in the framework. The proposed ontological framework is formalized using OWL(Ontology Web Language) and metrics selection rules satisfying the characteristics of R&D are represented in SWRL(Semantic Web Rule Language). Actual metrics selection procedure is carried out using JESS rule engine, a plug-in to Prot$\acute{e}$g$\acute{e}$, and illustrated with an example, incorporating a prevalent R&D performance model : TVP(Technology Value Pyramid).

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.426-431
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• 2011

The quality of performance evaluation on engineering consultants that provide design-related technical services is difficult to be measured, and only a handful of papers discussed the quality during the design stage. Although design cost is relatively far less than construction cost for a project, the decisions made in the design phase have a significant impact on the final products of the project, especially for large public construction projects. Therefore, this research focuses on reviewing and then establishing a performance evaluation framework for the consulting firms that execute detailed design and provide technical services for the Taipei Rapid Transit Systems (TRTS). By interviewing experts, this study first established a set of indicators to evaluate these firms' performance. Then, those indicators were incorporated into the four aspects of balanced scorecard (BSC) to establish the architecture of the evaluation mechanism. The weight of each indicator was calculated by analytic hierarchy process (AHP) from a survey conducted among experts. The results showed that the top-three indicators were quantity take-off, functions conformity, and budgeting. The framework of performance evaluation established by this study can be applied to measure service performance during the design stage. It not only facilitates the monitoring of consulting firms, but also helps to reduce unnecessary change orders and disputes during the construction stage.

• 한국시뮬레이션학회논문지
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• 제16권4호
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• pp.33-41
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• 2007

서비스 지향 아키텍처는 하나의 실체가 다른 하나의 실체를 대신해 단위 작업을 수행하도록 하는 방식으로 두 개의 컴퓨팅 실체가 상호작용 하는 방법을 정의한다. 이 단위 작업은 "서비스"라고 지칭되며, 이 서비스 상호작용들은 독립적이고 느슨한 결합을 가져야 한다. SOA의 이러한 특징인 느슨한 결합과, 높은 상호운영성의 효과는 서로 다른 이용자들이 서로 다른 방식으로 서비스와 의사소통을 하기 위해 얼마나 유연한 메시지 통신이 가능한가에 따라 결정된다. 본 논문에서는 .NET Framework를 이용한 WCF 기반의 메시징 프레임워크와 통합된 데이터 표현 방식을 이용하여 서비스 지향 아키텍처를 기반으로 한 웹 서비스 애플리케이션과 일반적인 웹 서비스에 대해 애플리케이션의 응답 성능 및 시스템의 안정성과 성능 지수를 비교 분석하였으며 그 결과를 통하여 WCF를 이용한 SOA환경의 웹 서비스가 가지는 장점을 확인하였다.

• 동아시아경상학회지
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• 제2권2호
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• pp.24-36
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• 2014

This study bridges the gap between management accounting, CG and entrepreneurship disciplines. Unlike previous studies, this study adopts a positivist approach to develop a contingency framework of CG that operationalises the conformance and performance dimensions into measurable constructs. The contingency framework also adopts a holistic approach that investigates the interrelationships between VBM, CG and CE, as important predictors of organizational performance, which can provide insights into the complementary or conflicting relationships among these predictors in their effects on organizational performance.

• 품질경영학회지
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• 제28권2호
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• pp.89-102
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• 2000

Many organizations have developed their own traditional quality information systems. But, they think of it as one of the functional information systems not as a company-wide decision support information systems. A study on traditional quality information systems(QIS) has been conducted and a new conceptual framework of quality information system is proposed in this paper. In order to support enterprise wide total quality management aggressively, a new conceptual framework, named quality management support information system(QMSIS) is developed and proposed. This framework is based upon Malcolm Baldrige National Quality Award(MBNQA) model integrates management information system approach and traditional quality information system concept. In this model, organizational performance and process performance can be monitored to support managers , decision making about organizational quality management activities.

• ETRI Journal
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• 제46권4호
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• pp.697-707
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• 2024

Music identification is widely regarded as a solved problem for music searching in quiet environments, but its performance tends to degrade in TV broadcast audio owing to the presence of dialogue or sound effects. In addition, constructing an accurate dataset for measuring the performance of background music monitoring in TV broadcast audio is challenging. We propose a framework for monitoring background music by automatic identification and introduce a background music cue sheet. The framework comprises three main components: music identification, music-speech separation, and music detection. In addition, we introduce the Cue-K-Drama dataset, which includes reference songs, audio tracks from 60 episodes of five Korean TV drama series, and corresponding cue sheets that provide the start and end timestamps of background music. Experimental results on the constructed and existing datasets demonstrate that the proposed framework, which incorporates music identification with music-speech separation and music detection, effectively enhances TV broadcast audio monitoring.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권6호
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• pp.637-647
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• 2010

최근 임베디드 시스템은 운영체제를 포함하는 복잡한 소프트웨어 계층 구조를 가지는 형태로 발전하고 있다. 이러한 소프트웨어의 성능을 분석하기 위해서는, 한 소프트웨어 계층에서의 성능 뿐 아니라 전체 소프트웨어 계층 구조를 모두 고려해야 한다. 본 논문에서는 리눅스 기반 임베디드 시스템의 모든 소프트웨어 계층 구조를 고려할 수 있는 성능 분석 도구를 설계하고 구현한 결과를 보인다. 제안하는 기법은 응용 프로그램이나 라이브러리에 대한 재컴파일 없이 모든 소프트웨어 계층의 성능 분석에 필요한 측정 정보를 수집한다. 이 기법을 통해 리눅스 기반 임베디드 시스템에서 응용 프로그램의 실행에 따라 발생하는 사용자 정의 함수, 미들웨어 라이브러리 함수, 커널의 시스템 호출, 커널 이벤트에 대한 다양한 성능 분석을 수행할 수 있다. 실험을 통해 본 연구를 통해 구현된 분석도구를 사용하여 실제 실행 경로 분석, 각 소프트웨어 계층의 함수나 이벤트의 소요시간 분석, 그리고 소프트웨어 계층간 실행 흐름 분석 결과를 확인할 수 있으며, 이를 통해 전체 소프트웨어 계층상의 성능 병목을 찾을 수 있음을 보인다.