• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3680-3693
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• 2022

The handover procedure of IEEE 802.11 wireless local area networks (WLANs) introduces significant delay, which can degrade the quality of service (QoS) especially for delay-sensitive applications. Although studies have been conducted to support handover in SDN-based WLAN, there is no research to reduce the channel scanning procedure that takes up the most delay time in the handover process. The channel scanning procedure is essential to determine the appropriate access point (AP). To mitigate this problem, this paper proposes a SWITCH: SDN-WLAN integrated handover scheme for QoS-Guaranteed mobile service. In SWITCH, each AP periodically broadcasts beacon frames through different channels in a predetermined order that includes the operating channel information of the AP. This allows mobile stations (MSs) to receive the beacon frames of nearby APs, and therefore they can determine the appropriate APs for handover without the channel scanning procedure. By reporting the information of the newly moved AP to the SDN controller, a flow rule is installed in advance to provide fast handover, and packet loss is reduced by buffering data destined for MS. In addition, the proposed scheme can adaptively operate SWITCH to consider the user location and QoS requirement of flow to save radio resource overhead. Performance evaluation results demonstrate that SWITCH can reduce the handover delays, flow table utilization ratio and radio resource overhead while improving the network throughput.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.7-12
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• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.61-67
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• 2022

The Internet of Things(IoT) is one of the key technologies in the Fourth Industrial Revolution. The IoT is a system that acquires information from various sensors and provides meaningful information to users. The method of obtaining information from sensor is using WIFI, Bluetooth and Server. is not accessible to external users because of different type of networks or local area communication. For this reason, there is a problem that external user cannot receive notification in regard to sensor information. In this paper, we want to establish a cloud message environment using Google's FCM(Firebase Cloud Messaging) and find out through experiments how users can receive notifications even if they are outside.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.644-647
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• 2004

Optical add/drop multiplexers (OADMs), one of the new network elements, will play a key role enabling greater connectivity and flexibility in the dense wavelength-division multiplexing (DWDM) networks. The importance of OADMs is that they allow the optical network to be local transmitting/extraction on a wavelength-by-wavelength basis to optimize traffic, efficient network utilization, network growth, and to enhance network flexibility. Also, the automatic assembly system of micro optical filters and fibers is a key technology in the development of optical modules with high functionality. Recently, one of remarkable tends in the development of optical communication industry is the miniaturization and integration of products. In this research, we have developed a system capable of automatic alignment of a film filter and a lensed fiber in order to improve the speed and losses in the optical fiber to filter alignment of optical modules. Using the developed automatic alignment system and silicon optical benches, we have fabricated the micro OADM and measured the insertion loss and aging effect.

• Annual Conference of KIPS
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• 2010.04a
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• pp.649-652
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• 2010

무선 센서 네트워크에서 클러스터링 기법은 데이터 병합을 통해 통신 대역폭 사용을 용이하게 하며, 센서 노드들간의 송수신 전력 소비를 줄일 수 있고, 노드 증가에 따른 네트워크 확장성이 용이하므로 현재 많은 연구가 되고 있다. 클러스터링 기법은 클러스터 헤더를 선출하는 것으로부터 시작된다. 기존의 클러스터 헤더 선출 기법들은 에너지 잔여량, 센서 노드의 위치, 센서 노드들의 평균 에너지 등을 클러스터 헤더 선출값으로 하여 클러스터 헤더를 선정한다. 그러나 이 기법들은 악의 적인 노드가 다른 노드의 클러스터 헤더 선출값을 변경하고, 자신의 클러스터 헤더 선출값을 증가시켜 클러스터 헤더가 될 수 있는 보안 취약점을 가지고 있다. 이와 같은 보안 취약점을 개선하기 위해 클러스터 헤더 선출값에 대한 무결성과 클러스터 헤더 선출값을 전송하는 노드의 인증이 필요하다. 본 논문에서는 one-way key chain 기법을 사용하는 안전한 클러스터 헤더 선출 기법을 제안하고, 제안한 기법에 대한 안전성을 분석한다.

• Annual Conference of KIPS
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• 2009.04a
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• pp.1214-1217
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• 2009

무선 센서 네트워크에서 각각의 센서 노드들은 무선 통신을 통해 서로 간에 통신을 수행한다. 과거에는 이러한 센서 노드간의 통신을 제 3 자로부터 안전하게 지키는 것이 중요한 보안 이슈였다. 특히 보안 서비스를 제공 하기 위한 키 관리 기법들이 주요 연구방향이었다. 하지만 안전하게 만들어진 확률론적 키(key)를 기반으로 하는 키 사전분배 방법은 공격받은 다른 노드로 인해 자신의 키가 노출 될 수 있다. 공격자는 노출된 공유키(shared key)를 통해 노출되지 않은 정상 노드(non-compromised node) 사이의 대칭키(pairwise key)를 얻을 수 있으며, 공격자는 네트워크에 심각한 영향을 줄 수 있는 메시지 삽입 및 수정 공격을 감행할 수 있다. 이와 같은 오용된 키를 폐기하고 메시지 삽입 및 수정 공격을 막기 위해 Liu and Dong 은 오용키 탐지 방법을 제안하였다. 하지만 이들의 방법에는 한계점이 있어 이를 보완하기 위한 에너지 효율적인 오용키 탐지 기법을 제안한다.

• Annual Conference of KIPS
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• 2009.04a
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• pp.720-723
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• 2009

기존에 제안된 클러스터 기반의 데이터 전송 프로토콜은 데이터 전송을 위해 헤더 노드가 존재하고 각 헤더노드는 데이터 전송을 위한 경로 정보를 유지해야 하기 때문에 전송할 데이터가 많아지면 저장해야 할 캐시도 증가하게 되고 데이터 전송 시 데이터 공고와 요구의 과정을 거쳐야 된다. 또한 LOAD(6LoWPAN Ad hoc Routing Protocol)에서는 데이터 전송 시 목적지에 대한 경로 정보를 획득 하는 작업과 획득한 경로를 테이블에 보관해야 하는 단점이 있다. 본 논문에서 제안된 데이터 전송 프로토콜은 데이터 전송 요구 시 목적지로 전송하기 위한 경로 정보의 획득이나 유지를 하지 않는다. 또한 노드들이 한번씩 데이터를 전송함으로써 노드의 전체적인 에너지 공평성과 효율성을 증가시키고, 전체 네트워크의 수명을 연장 시킬 수 있다.

• Annual Conference of KIPS
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• 2009.11a
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• pp.547-548
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• 2009

The development of USN(Ubiquitous Sensor Network) technology is creating numerous application areas. Although a network configuration with fixed sensors was the norm in the past, the coexistence of mobile and fixed sensor nodes is a new trend. Fixed sensor networks focused on the energy efficiency of nodes, but the latest studies consider guaranteeing the mobility of nodes and maintaining their connectivity, while remaining energy efficient at the same time. This paper proposes a routing protocol for a mobile ad-hoc sensor network that improves the mobility, connectivity and energy efficiency of nodes while allowing for the management and maintenance of a large number of nodes even in a complex communication environment where mobile and fixed nodes coexist. An algorithm for multi-hop multi-paths, a technique for topology reconfiguration by node movement prediction and vibration sensors, path setting for a large number of nodes, and efficient data transfer technology have been introduced to implement the modified LEAHC-AOMDV protocol. Furthermore, the excellence of this protocol was verified through a comparative experiment with the conventional LEACH protocol.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.53-58
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• 2023

With the fast development of artificial intelligence day by day, users are demanding explanations about the results of algorithms and want to know what parameters influence the results. In this paper, we propose a model for bankruptcy prediction with interpretability using the SHAP framework. SHAP (SHAPley Additive exPlanations) is framework that gives a visualized result that can be used for explanation and interpretation of machine learning models. As a result, we can describe which features are important for the result of our deep learning model. SHAP framework Force plot result gives us top features which are mainly reflecting overall model score. Even though Fully Connected Neural Networks are a "black box" model, Shapley values help us to alleviate the "black box" problem. FCNNs perform well with complex dataset with more than 60 financial ratios. Combined with SHAP framework, we create an effective model with understandable interpretation. Bankruptcy is a rare event, then we avoid imbalanced dataset problem with the help of SMOTE. SMOTE is one of the oversampling technique that resulting synthetic samples are generated for the minority class. It uses K-nearest neighbors algorithm for line connecting method in order to producing examples. We expect our model results assist financial analysts who are interested in forecasting bankruptcy prediction of companies in detail.