• Title/Summary/Keyword: Cluster Systems

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A study of Mesoscale Convective Systems(MCSs) event impacts on the safe operation of aircraft(II) (항공기 안전 운항에 영향을 미치는 중규모 대류계 사례 연구(II))

  • Kim, Young-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.22 no.2
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    • pp.40-47
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    • 2014
  • Heavy Rainfall event accompanying with Mesoscale Convective Systems(MCSs) inducing flash flooding and Muan and Kunsan Airport closing over Jeollabuk-do area was investigated this study. Comparing to previous study(I), this heavy rainfall event was characterized by much abundant moisture from Typhoon, strong conditional convective instability, and cluster type MCSs. It almost impossible to make accurate forecasting of precipitation amounts and life cycle of MCSs unless proper analysis.

Predictive Analysis of Financial Fraud Detection using Azure and Spark ML

  • Priyanka Purushu;Niklas Melcher;Bhagyashree Bhagwat;Jongwook Woo
    • Asia pacific journal of information systems
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    • v.28 no.4
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    • pp.308-319
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    • 2018
  • This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

Autonomic Self Healing-Based Load Assessment for Load Division in OKKAM Backbone Cluster

  • Chaudhry, Junaid Ahsenali
    • Journal of Information Processing Systems
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    • v.5 no.2
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    • pp.69-76
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    • 2009
  • Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.

Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems (배전계통 최적 재구성 문제에 PC 클러스터 시스템을 이용한 병렬 유전 알고리즘-타부 탐색법 구현)

  • Mun Kyeong-Jun;Song Myoung-Kee;Kim Hyung-Su;Kim Chul-Hong;Park June Ho;Lee Hwa-Seok
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.53 no.10
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    • pp.556-564
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    • 2004
  • This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems

  • Mun Kyeong-Jun;Lee Hwa-Seok;Park June-Ho
    • KIEE International Transactions on Power Engineering
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    • v.5A no.2
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    • pp.116-124
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    • 2005
  • This paper presents an application of the parallel Genetic Algorithm-Tabu Search (GA- TS) algorithm, and that is to search for an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration of distribution systems is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to solve the optimal switch position because of its numerous local minima. This paper develops a parallel GA- TS algorithm for the reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10$\%$ of the population to enhance the local searching capabilities. With migration operation, the best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based rapid Ethernet. To demonstrate the usefulness of the proposed method, the developed algorithm was tested and is compared to a distribution system in the reference paper From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution quality, speedup, efficiency, and computation time.

A Dynamic Work Manager for Heterogeneous Cluster Systems (DWM: 이기종 클러스터 시스템의 동적 자원 관리자)

  • Park, Jong-Hyun;Kim, Jun-Seong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.6
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    • pp.56-62
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    • 2009
  • Inexpensive high performance computer systems combined with high speed networks and machine independent communication libraries have made cluster computing a viable option for parallel applications. In a heterogeneous cluster environment, efficient resource management is critically important since the computing power of the individual computer system is a significant performance factor when executing applications in parallel. This paper presents a dynamic task manager, called DWM (dynamic work manager). It makes a heterogeneous cluster system fully utilize the different computing power of its individual computer system. We measure the performance of DWM in a heterogeneous cluster environment with several kernel-level benchmark programs and their programming complexity quantitatively. From the experiments, we found that DWM provides competitive performance with a notable reduction in programming effort.

On the Handling of Node Failures: Energy-Efficient Job Allocation Algorithm for Real-time Sensor Networks

  • Karimi, Hamid;Kargahi, Mehdi;Yazdani, Nasser
    • Journal of Information Processing Systems
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    • v.6 no.3
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    • pp.413-434
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    • 2010
  • Wireless sensor networks are usually characterized by dense deployment of energy constrained nodes. Due to the usage of a large number of sensor nodes in uncontrolled hostile or harsh environments, node failure is a common event in these systems. Another common reason for node failure is the exhaustion of their energy resources and node inactivation. Such failures can have adverse effects on the quality of the real-time services in Wireless Sensor Networks (WSNs). To avoid such degradations, it is necessary that the failures be recovered in a proper manner to sustain network operation. In this paper we present a dynamic Energy efficient Real-Time Job Allocation (ERTJA) algorithm for handling node failures in a cluster of sensor nodes with the consideration of communication energy and time overheads besides the nodes' characteristics. ERTJA relies on the computation power of cluster members for handling a node failure. It also tries to minimize the energy consumption of the cluster by minimum activation of the sleeping nodes. The resulting system can then guarantee the Quality of Service (QoS) of the cluster application. Further, when the number of sleeping nodes is limited, the proposed algorithm uses the idle times of the active nodes to engage a graceful QoS degradation in the cluster. Simulation results show significant performance improvements of ERTJA in terms of the energy conservation and the probability of meeting deadlines compared with the other studied algorithms.

Regional Innovation Systems of the California Wine Cluster: the Case of Napa and Sonoma (미국 캘리포니아의 와인생산 클러스터에 관한 연구: 나파.소노마 지역을 사례로)

  • Shin, Dong-Ho
    • Journal of the Economic Geographical Society of Korea
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    • v.11 no.1
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    • pp.130-147
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    • 2008
  • Spanish missionaries started to grow vine grapes and make wines in California 230 years ago. Earlier pioneers of the land started to do the same works for commercial purposes 130 years ago. Now California became one of the most important wine making places of the world. The quality of California wines in fact have been acknowledged as the best in the world by being ranked on the top in international wine tasting competition, such as Paris Tasting. A large wine cluster, consisted of grape growing, wine making, wine tours, and research and education, has been created in the area centered by Napa and Sonoma, California. In this context, this paper examines the process of formulating the cluster, factors contributing the success, articulates core actors, and draws policy and theoretical implications. It concludes that innovative actors, such as winery founders, local universities, and business organizations, have played key roles in establishing the California wine cluster.

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Draft Design of DataLake Framework based on Abyss Storage Cluster (Abyss Storage Cluster 기반의 DataLake Framework의 설계)

  • Cha, ByungRae;Park, Sun;Shin, Byeong-Chun;Kim, JongWon
    • Smart Media Journal
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    • v.7 no.1
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    • pp.9-15
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    • 2018
  • As an organization or organization grows in size, many different types of data are being generated in different systems. There is a need for a way to improve efficiency by processing data smarter in different systems. Just like DataLake, we are creating a single domain model that accurately describes the data and can represent the most important data for the entire business. In order to realize the benefits of a DataLake, it is import to know how a DataLake may be expected to work and what components architecturally may help to build a fully functional DataLake. DataLake components have a life cycle according to the data flow. And while th data flows into a DataLake from the point of acquisition, its meta-data is captured and managed along with data traceability, data lineage, and security aspects based on data sensitivity across its life cycle. According to this reason, we have designed the DataLake Framework based on Abyss Storage Cluster.

A Framework for Success of Industrial Clusters: The Fusion of Online and Offline Businesses (온라인과 오프라인이 융합된 성공적 산업클러스터의 프레임워크)

  • Yi Jung-Sub;Jang Hyeong-Wook
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.3
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    • pp.96-107
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    • 2006
  • This paper explores the benefits provided by the adoption and implementation of electronic commerce in a particular SME-intensive productive environment: the geographical cluster. This study develops a conceptual framework that highlights the six types of benefits obtained by integrating online business with offline business. Using data from 73 traditional companies in Korean port clusters, factor analysis was used to figure out six benefits including sharing information, cost savings, value-added service, customer relationship, enhanced trust, and marketing efficiency. The six empirically derived critical benefit factors were then used to examine how they improve management performance of the traditional offline companies in the cluster measured by Balanced Scorecard(BSC). According to the results, we concluded that the offline firms in the cluster can take advantages of extending to online business.

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