• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.314-317
• /
• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.6
• /
• pp.2513-2533
• /
• 2018

In cognitive radio technology, the overall efficiency of communications systems can be improved without allocating additional bands by allowing a secondary system to utilize the licensed band when the primary system, which has the right to use the band, does not use it. In this paper, we propose a fast and reliable common channel initialization protocol without any exchange of initialization messages between the cluster head and the member nodes in cognitive ad-hoc networks. In the proposed method, the cluster and member nodes perform channel-based spectrum sensing. After sensing, the cluster head transmits a system activation signal through its available channels with a predetermined angle difference pattern. To detect the cluster head's transmission channels and to join the cluster, each member node implements fast Fourier transform (FFT) and computes autocorrelation for the angle difference sequence of the received signal patterns. This is compared to the predetermined reference angle difference pattern. The join-request and channel-decision procedures are presented in this paper. Performance evaluation of the proposed method is presented in the simulation results.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.3
• /
• pp.169-175
• /
• 2010

Recently, to improve operating efficiency with the higher in-line rate in automated production lines, a lot of cases of grouping machines and material handling system together to form a cluster has shown frequently. This article addresses the job allocation and operation method of automated material handling for cluster-type production systems. First of all, the control problems of the automated material handling systems are classified into the control problem of inter-cluster material handling system and that of intra-cluster material handling system. Then, a distributed agent-based control scheme is proposed for the former, and an operational control procedure for the latter. Simulation experiment shows that the proposed method is efficient in reducing cycle times and improving utilization of material handling vehicles.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.6
• /
• pp.639-646
• /
• 2002

In this paper, we discuss the system configuration and the design issues of CATS-i, a set of installation and administration tools for Linux cluster systems. CATS-i enables users to manage cluster systems easily, quickly, and safety. It integrates many functions, ranging from installing operating systems and applications to real-time monitoring and management of various important resources. In addition, batch job submission and management are included. These functions support a single system image. Finally, a powerful graphic user interface based on Java lets users quickly understand the cluster status and conveniently use the CATS-i on the Web.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.10
• /
• pp.533-543
• /
• 2003

With the increase of interests in cluster, there have been a number of research efforts to address the high availability issues on cluster. However, there are no kernel-level group communication systems to support the development of kernel-level application programs and it is not easy to use traditional user-level group communication systems for the kernel-level applications. This paper presents the design and implementation issues of KCGCS(Kernel-level Cluster Group Communication System), which is a kernel-level group communication module for linux cluster. Unlike traditional user-level group communication systems, the KCGCS uses light-weight heartbeat messages and a ring-based heartbeat mechanism, which allows users to implement scalable failure detection mechanisms. Moreover, the KCGCS improves the reliability by using distributed coordinators to maintain membership information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.435-437
• /
• 2016

Hadoop Distributed File System(HDFS) is a file system for distributed processing of big data by replicating data to distributed data nodes. HDFS cluster shows a great scalability up to thousands of nodes, but it assumes a exclusive node cluster with numerous nodes for the big data processing. Various operational-purpose worker systems used by office are hardly considered as a part of cluster. This paper discusses this problem and proposes a dynamic cluster management technique to increase storage capability and analytic performance of hadoop cluster. The propsed technique can add legacy systems to the cluster and can remove them from the cluster dynamically depending on their availability.

• Journal of computational fluids engineering
• /
• v.6 no.2
• /
• pp.47-55
• /
• 2001

In recent years cluster systems using off-the-shelf processors and networks components have been increasing popular. Since actual performance of a cluster system varies significantly for different architectures, representative in-house codes from major application fields were executed to evaluate the actual performance of systems with different combination of CPU, network, and network topology. As an example of practical CFD(Computational Fluid Dynamics) simulations, the flow past an Onera-M6 wing and the flow past an infinite wing were simulated on clusters of Linux and several other hardware environments.

• Journal of Information Technology Services
• /
• v.7 no.1
• /
• pp.195-204
• /
• 2008

As the dependency to network system and demands of efficient storage systems rapidly grows in every networking filed, the current trends initiated by explosive networked data grow due to the wide-spread of internet multimedia data and internet requires a paradigm shift from computing-centric to data-centric in storage systems. Furthermore, the new environment of file systems such as SAN(Storage Area Network) is adopted to the existing storage paradigm for providing high availability and efficient data access. We describe the design issues and system components of $SANique^{TM}$, which is the cluster file system based on SAN environment. We, especially, present the comparative results of performance analysis for the intensive I/O test by using the DBMSs that are operated at the top of cluster file system $SANique^{TM}$, EXT3 and NFS respectively.

• Journal of information and communication convergence engineering
• /
• v.20 no.2
• /
• pp.96-102
• /
• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.9
• /
• pp.445-453
• /
• 2003

As cluster systems used for high performance computing consist of large number of running servers, one has to solve the low availability problems occurred by the high chance of the server failures. To handle the problems, it is necessary to have the precise definition of available performance of cluster systems that represents availability and performability of the systems simultaneously. Previous research results that mention availability issues lack for concerning system performance such as waiting time and response time in their availability definition. In this paper, we propose a new availability metric for (n, k)-way cluster systems which compose of n primary servers and k backup servers. With the metric, the change of system performance according to arrival rates is captured and the waiting time of a request can be kept below to a certain level. Using various system operating parameters, we calculate availability and downtime of cluster systems along with waiting tine deadline.