• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.141-146
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• 2024

A local area network (LAN) is a computer network within a small geographical area such as a home, school, computer laboratory, office building or group of buildings. A LAN is composed of interconnected workstations and personal computers which are each capable of accessing and sharing data and devices, such as printers, scanners and data storage devices, anywhere on the LAN. LANs are characterized by higher communication and data transfer rates and the lack of any need for leased communication lines. Communication between remote parties can be achieved through a process called Networking, involving the connection of computers, media and networking devices. When we talk about networks, we need to keep in mind three concepts, distributed processing, network criteria and network structure. The purpose of this Network is to design a Local Area Network (LAN) for a BAEC (Bangladesh Atomic Energy Commission) Head Quarter and implement security measures to protect network resources and system services. To do so, we will deal with the physical and logical design of a LAN. The goal of this Network is to examine of the Local Area Network set up for a BAEC HQ and build a secure LAN system.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.611-618
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• 2016

The suggested paper studies communications network and system technology, designing data to sync to both USB memories and cloud storages at the same time, which would allow users to safely keep and manage data even in case of network troubles, affecting cloud storages, and/or loss of physical USB memories, resulting in lost data in the physical memory. The need of secure data management policy for cloud storage users form the basis of this study, offering solutions to network failures and loss of physical storage by creating hybrid cloud system. To provide convenience to windows users, the UI design should integrate that of windows explorer to maximize security and convenience.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.32-41
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• 2006

In data-centric networks, various data items, such as temperature, humidity, etc. are sensed and stored in sensor nodes. As these attributes are mostly scalar values and inter-related, multi-dimensional range queries are useful. To process multi-dimensional range queries efficiently in data-centric storage, data addressing is essential. The Previous work focused on efficient query processing without considering overall network lifetime. To prolong network lifetime and support multi-dimensional range queries, we propose a dynamic data distribution method for multi-dimensional data, where data space is divided into equal-sized regions and linearized by using Hilbert space filling curve.

• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.261-269
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• 2023

We propose to design a Holochain-based security and privacy protection system for resource-constrained IoT healthcare systems. Through analysis and performance evaluation, the proposed system confirmed that these characteristics operate effectively in the IoT healthcare environment. The system proposed in this paper consists of four main layers aimed at secure collection, transmission, storage, and processing of important medical data in IoT healthcare environments. The first PERCEPTION layer consists of various IoT devices, such as wearable devices, sensors, and other medical devices. These devices collect patient health data and pass it on to the network layer. The second network connectivity layer assigns an IP address to the collected data and ensures that the data is transmitted reliably over the network. Transmission takes place via standardized protocols, which ensures data reliability and availability. The third distributed cloud layer is a distributed data storage based on Holochain that stores important medical information collected from resource-limited IoT devices. This layer manages data integrity and access control, and allows users to share data securely. Finally, the fourth application layer provides useful information and services to end users, patients and healthcare professionals. The structuring and presentation of data and interaction between applications are managed at this layer. This structure aims to provide security, privacy, and resource efficiency suitable for IoT healthcare systems, in contrast to traditional centralized or blockchain-based systems. We design and propose a Holochain-based security and privacy protection system through a better IoT healthcare system.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.61-68
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• 2013

Long-term runoff model can be used to establish the effective plan of water reources allocation and the determination of the storage capacity of reservoir. So this study aims at the development of monthly runoff model using artificial neural network technique. For this, it was selected multi-layer neural network(MLN) and radial basis function neural network(RFN) model. In this study, it was applied model to analysis monthly runoff process at the Wi stream basin in Nakdong river which is representative experimental river basin of IHP. For this, multi-layer neural network model tried to construct input 3, hidden 7, and output 1 for each number of layer. As the result of analysis of monthly runoff process using models connected with artificial neural network technique, it showed that these models were effective in the simulation of monthly runoff.

• Water for future
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• v.29 no.4
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• pp.109-118
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• 1996

The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.141-149
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• 2024

This paper proposes a configuration automation technique to minimize service interruption time in the event of a corporate network access layer switch failure. The automation is achieved without the need for a separate external system, as the network setting information is stored in a container inside the switch, enabling rapid recovery without requiring separate storage. This approach ensures the continuity of network services and demonstrates the efficiency of configuration automation. The proposed technique improves corporate network stability by providing a quick response in the event of a failure.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.99-113
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• 2004

A new architecture called SAN(Storage Area Network) was developed in response to the requirements of high availability of data, scalable growth, and system performance. In order to use SAN more efficiently, most of SAN operating softwares support storage virtualization concepts that allow users to view physical storage devices attached to SAN as a large volume virtually h logical volume manager plays a key role in storage virtualization. It realizes the storage virtualization by mapping logical addresses to physical addresses. A logical volume manager also supports a snapshot that preserves a volume image at certain time and on-line reorganization to allow users to add/remove storage devices to/from SAN even while the system is running. To support the snapshot and the on-line reorganization, most logical volume managers have used table based mapping methods. However, it is very difficult to manage mapping table because the mapping table is large in proportion to a storage capacity. In this paper, we design and implement an efficient and flexible hybrid mapping method based on mathematical equations. The mapping method in this paper supports a snapshot and on-line reorganization. The proposed snapshot and on-line reorganization are performed on the reserved area which is separated from data area of a volume. Due to this strategy normal I/O operations are not affected by snapshot and reorganization. Finally, we show the superiority of our proposed mapping method through various experiments.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.55-59
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• 2010

Most applications for solar-powered wireless sensor networks are usually deployed in remote areas without a continuous connection to the external networks and a regular maintenance by an administrator. In this case, sensory data has to be stored in the network as much as possible until it is uploaded by the data mule. For this purpose, a balanced data distribution over the network should be performed, and this can be achieved efficiently by taking the amount of available energy and storage into account, in the system layer of each node. In this paper, we introduce a simple but very efficient data distribution algorithm, by which each solar-powered node utilizes the harvested energy and the storage space maximally. This scheme running on each node determines the amount of energy which can be used for a data distribution as well as the amount of data which should be transferred to each neighbor, by using the local information of energy and storage status.