• Journal of Industrial Convergence
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• v.21 no.5
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• pp.133-142
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• 2023

In recent years, the problem of academic credential falsification is not simply the manipulation of certificates generated by educational institutions, but also the difficulty of trusting automated relationship verification and verification itself, such as falsely recording completion as graduation while still in school. This is due to the lack of sharing of educational background databases among university institutions and the establishment/operation of independent systems that make it difficult to track educational backgrounds. This study designs and implements an E-AV model for academic credential verification centered on university institutions. It summarizes and stores the linked information on the existing academic background in an encrypted database and implements it with web standard technology considering the compatibility and scalability of the existing system. The results of sample data verification show that it improves safety against forgery and complies with storage space and execution performance. This study aims to contribute to the improvement of online verification services such as academic records management in domestic universities.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1087-1094
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• 2023

Due to the development of technologies, such as big data, cloud, IoT, and AI, The high data throughput is required, and the importance of network flexibility and scalability is increasing. However, existing network systems are dependent on vendors and equipment, and thus have limitations in meeting the foregoing needs. Accordingly, SDN technology that can configure a software-centered flexible network is attracting attention. In particular, a load balancing method based on SDN can efficiently process massive traffic and optimize network performance. In the existing load balancing studies in SDN environment have limitation in that unnecessary traffic occurs between servers and controllers or performing load balancing only after the server reaches an overload state. In order to solve this problem, this paper proposes a method that minimizes unnecessary traffic and appropriate load balancing can be performed before the server becomes overloaded through a method of assigning weights to servers in stages according to server load.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.92-103
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• 2010

The Web Ontology Language (OWL) has become the W3C recommendation for publishing and sharing ontologies on the Semantic Web. To derive hidden information from OWL data, a number of OWL reasoners have been proposed. Since OWL reasoners are memory-based, they cannot handle large-sized OWL data. To overcome the scalability problem, RDBMS-based systems have been proposed. These systems store OWL data into a database and perform reasoning by incorporating the use of a database. However, they do not consider complete reasoning on all types of properties defined in OWL and the database schemas they use are ineffective for reasoning. In addition, they do not manage updates to the OWL data which can occur frequently in real applications. In this paper, we compare various database schemas used by RDBMS-based systems and propose an improved schema for efficient reasoning. Also, to support reasoning for all the types of properties defined in OWL, we propose a complete and efficient reasoning algorithm. Furthermore, we suggest efficient approaches to managing the updates that may occur on OWL data. Experimental results show that our schema has improved performance in OWL data storage and reasoning, and that our approaches to managing updates to OWL data are more efficient than the existing approaches.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.353-358
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• 2015

The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. In this case, reconstructing the system in order to add or extend a range of vocabulary is a way to solve the problem. This paper propose configured Bhattacharyya algorithm standing by speech recognition learning model using the Bayesian methods which reflect parameter estimation upon the model configuration scalability. It is recognized corrected standard model based on a characteristic of the phoneme using the Bayesian methods for parameter estimation of the phoneme's data and Bhattacharyya algorithm for a similar model. By Bhattacharyya algorithm to configure recognition model evaluates a recognition performance. The result of applying the proposed method is showed a recognition rate of 97.3% and a learning curve of 1.2 seconds.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.2 s.344
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• pp.51-59
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• 2006

Von Neumann architecture suffers from the interface between the central processing unit and the memory, which is called 'Von Neumann bottleneck' In this paper, we propose a scalable general-purpose associative processor (AP) based on content-addressable memory (CAM) which solves this problem and is suitable for the search-oriented applications. We propose an efficient instruction set and a structural scalability to extend for larger applications. We define twelve instructions and provide some reduced instructions to speed up which execute two instructions in a single instruction cycle. The proposed AP performs in a bit-serial, word-parallel fashion and can be considered as a 32-bit general-purpose parallel processor with a massively parallel SIMD structure. We design and simulate a maximum/minumum search greater-than/less-than search, and parallel addition to verify the proposed architecture. The algorithms are executed in a constant time O(k) regardless of the number of input data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.108-113
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• 2003

Research results have demonstrated that conventional client-server databases have scalability problem in the presence of many concurrent clients. The multi-tier architecture that exploits similarities in clients' object access behavior partitions clients into logical clusters according to their object request pattern. As a result, object requests that are served inside the clusters, server load and request response time can be optimized. Management of clustering by utilizing clients' access pattern-based is an important component for the system's goal. Off-line methods optimizes the quality of the global clustering, the necessary cost and clustering schedule needs to be considered and planned carefully in respect of stable system's performance. In this paper, we propose methods that detect changes in access behavior and optimize system configuration in real time. Finally this paper demonstrates the effectiveness of on-line change detection and results of experimental investigation concerning reconfiguration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.676-682
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• 2018

As the IoT world including WSNs develops, the number of sensor systems that sense information according to the environment based on the principle of IoT is increasing. In order to perform security for each sensor system in such a complicated environment, the security modules must be varied. These problems make hardware/software implementation difficult when considering the system efficiency and hacking/cracking. Therefore, to solve this problem, this paper proposes a pseudorandom number generator (FLT: Pseudo-random Number Generator with Fixed Length Tap unrelated to the variable sensing nodes) with a fixed-length tap that generates a pseudorandom number with a constant period, irrespective of the number of sensing nodes, and has the purpose of detecting anomalies. The proposed FLT-LFSR architecture allows the security level and overall data formatting to be kept constant for hardware/software implementations in an IoT environment. Therefore, the proposed FLT-LFSR architecture emphasizes the scalability of the network, regardless of the ease of implementation of the sensor system and the number of sensing nodes.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.296-301
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• 2016

Object-based storage is an efficient storage solution that can handle unstructured data and shows better security and scalability than traditional block-based storage. However, in terms of power management, Object-based storage writes multiple copies in storage cluster, hence many servers consume unnecessary power in idle state. In order to resolve this problem, it is necessary to apply power management strategy by adjusting power mode of servers in idle state according to their workloads. In this paper, we proposed a new dynamic power management (DPM) method to transform power mode of storage servers dynamically according to workload information sent from proxy server. The experimental result shows that the proposed power management technic reduces total power consumption by 12% in the OpenStack based Swift object storage.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.91-105
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• 2010

A wireless sensor network communication technique has been broadly studied with continuous advances in ubiquitous computing environment. Especially, because the resource of the sensor node is limited, it is important to reduce the communication energy by using an energy-efficient routing protocol. The existing cluster-based routing protocols have a problem that they cannot select a cluster head efficiently by randomly choosing a head. In addition, because the existing cluster-based routing protocols do not support the large scale of network, they cannot be used for various applications. To solve the above problems, we, in this paper, propose a new cluster-based routing protocol using representative paths. The proposed protocol constructs an efficient cluster with distributed cluster heads by creating representative paths based on hop count. In addition, a new routing protocol supports multi-hop routing for data communication between a cluster member node and a cluster head as well as between cluster heads. Finally, we show that our protocol outperforms LEACH and Multihop-LEACH in terms of reliability and scalability.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.204-212
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• 2011

Mobile P2P(Peer-to-Peer) protocols in MANET(mobile ad-hoc networks) have gained much attention recently. Existing P2P protocols can be categorized into structured and unstructured ones. In MANET, structured P2P protocols show large control traffic because they does not consider the locality of P2P data and unstructured P2P protocols have a scalability problem with respect to the number of nodes. Hybrid P2P protocols combine advantages of the structured and unstructured P2P protocols. Cluster-based P2P protocol is one of the hybrid P2P protocols. Our study makes an analysis of the cluster-based P2P protocol and derives the optimal cluster formation in MANET. In the derived optimal cluster formation, the cluster-based P2P protocol shows better performance than Gnutella protocol with respect to control traffic.