• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.371-382
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• 2007

Modern server systems are usually composed in the form of cluster systems in order to serve not only as many users but also as many kinds of applications as possible. The progression of the cluster system architecture leads in a middleware approach based on the Java framework. The middleware approach alleviates the efforts for the construction and the management of a server system but still preserves its performance and applications on the server. In this research, we introduce a new clustering scheme for the easy construction and maintenance of a cluster server system with the Java Management Extensions. We first demonstrate the construction and configuration process. Our experiment sets can verify that it is easy to construct, expand and manage a middleware based cluster system as well as the applications which reside on it. In addition, we can achieve reasonable performance on our service oriented clustered system with the help of state-of-the-art middleware. The experimental results of performance demonstration contain the availability of a server, and the effectiveness of load balancing and scheduling mechanisms. Especially, our service oriented scheduling mechanism was shown to successfully manage load imbalance under the normal load and cope with the overloaded situations, compared with other known scheduling mechanisms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1999-2007
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• 2007

This article describes advanced clover algorithm for effective loading and unloading of containers using stackers position data in a yard. The job scheduling must rely on job assign of stackers and position data processing to dynamically allocate stackers, and maintain multiple job processing, all based on task requirements. A stacker tracking using GPS and GIS is an essential capability and is used as yard loading and unloading process improvement for yard management. After estimating position of stackers in a yard the raper describes advanced clover algorithm and other techniques for monitoring loading and unloading of individual containers as well as combinatorial stacker load balancing problems such as estimating load of each stackers. Results from simulations and experimental implementations have demonstrated that the suggested approaches are efficient in stacker management.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.418-429
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• 2001

Recently, a GIS has been applicable to the most important computer applications such as urban information systems and transportation information systems. These applications require spatial operations for an efficient management of a large volume of data. In particular, a spatial join among basic operations has the property that its response time is increased exponentially according to the number of spatial objects included in the operation. Therefore, it is not proper to the systems demanding the fast response time. To satisfy these requirements, the efficient parallel processing of spatial joins has been required. In this paper, the efficient method for creating and allocating tasks to balance statically the load of each processor in a parallel spatial join is presented. A task graph is developed in which a vertex weight is calculated by the cost model I have proposed. Then, it is partitioned through a graph partitioning algorithm. According to the experiments in CC16 parallel machine, our method made an improvement in the static load balance by decreasing the variance of a task execution time on each processor.

• Atmosphere
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• v.29 no.1
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• pp.75-86
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• 2019

In this paper, we introduce a novel Climate & Environment Database System (CEDS). The CEDS is developed by the National Institute of Meteorological Sciences (NIMS) to provide easy and efficient user interfaces and storage management of climate model data, so improves work efficiency. In uploading the data/files, the CEDS provides an option to automatically operate the international standard data conversion (CMORization) and the quality assurance (QA) processes for submission of CMIP6 variable data. This option increases the system performance, removes the user mistakes, and increases the level of reliability as it eliminates user operation for the CMORization and QA processes. The uploaded raw files are saved in a NAS storage and the Cassandra database stores the metadata that will be used for efficient data access and storage management. The Metadata is automatically generated when uploading a file, or by the user inputs. With the Metadata, the CEDS supports effective storage management by categorizing data/files. This effective storage management allows easy and fast data access with a higher level of data reliability when requesting with the simple search words by a novice. Moreover, the CEDS supports parallel and distributed computing for increasing overall system performance and balancing the load. This supports the high level of availability as multiple users can use it at the same time with fast system-response. Additionally, it deduplicates redundant data and reduces storage space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.277-280
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• 2015

Smishing, Phishing personal privacy caused by Incident accidents such as Phishing information security has become a hot topic. Such incidents have privacy in personal information management occurs due to a lack of user awareness. This paper is based on the existing structure of the XML Tag question bank used a different Key-Value Structure-based JSON. JSON is an advantage that does not depend on the language in the text-based interchange format. The proposed system is divided into information security sector High, Middle and Low grade. and Provides service to the user through the free space and the smart device and the PC to the constraints of time. The use of open source Apache Load Balancing technology for reliable service. It also handles the user's web page without any training sessions Require server verification result of the training(training server). The result is sent to the training server using jQuery Ajax. and The resulting data are stored in the database based on the user ID. Also to be used as a training statistical indicators. In this paper, we design a level training system to enhance the user's information security awareness.

• Journal of Astronomy and Space Sciences
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• v.28 no.3
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• pp.241-252
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• 2011

A simulated network protocol provides the capability of distributed simulation to a generic simulator. Through this, full coverage of management of data and service handling among separated simulators is achieved. The distributed simulation environment is much more conducive to handling simulation load balancing and hazard treatment than a standalone computer. According to the simulated network protocol, one simulator takes on the role of server and the other simulators take on the role of client, and client is controlled by server. The purpose of the simulated network protocol is to seamlessly connect multiple simulator instances into a single simulation environment. This paper presents the development of a simulated network (simNetwork) that provides the capability of distributed simulation to a generic simulator (GenSim), which is a software simulator of satellites that has been developed by the Korea Aerospace Research Institute since 2010, to use as a flight software validation bench for future satellite development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5419-5436
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• 2016

Enhancing the performance of computing systems has been an important topic since the invention of computers. The leading-edge technologies of multicore and virtualization dramatically influence the development of current IT systems. We study performance attributes of response time (RT), throughput, efficiency, and scalability of a virtualized Web system running on a multicore server. We build virtual machines (VMs) for a Web application, and use distributed stress tests to measure RTs and throughputs under varied combinations of virtual cores (VCs) and VM instances. Their gains, efficiencies and scalabilities are also computed and compared. Our experimental and analytic results indicate: 1) A system can perform and scale much better by adopting multiple single-VC VMs than by single multiple-VC VM. 2) The system capacity gain is proportional to the number of VM instances run, but not proportional to the number of VCs allocated in a VM. 3) A system with more VMs or VCs has higher physical CPU utilization, but lower vCPU utilization. 4) The maximum throughput gain is less than VM or VC gain. 5) Per-core computing efficiency does not correlate to the quality of VCs or VMs employed. The outcomes can provide valuable guidelines for selecting instance types provided by public Cloud providers and load balancing planning for Web systems.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.101-108
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• 2017

A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.

• ETRI Journal
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• v.42 no.5
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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.