• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.81-83
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• 2023

태양 에너지 수집형 IoT 기기는 주기적으로 재충전되는 태양 에너지의 특성상, 에너지 소모를 최소화하기보다는 수집된 에너지를 최대한 유용하게 사용하는 것이 중요하다. 한편, 데이터 기밀성과 프라이버시, 응답속도, 비용 등의 이유로 클라우드가 아닌 데이터 소스 근처에서 머신러닝을 수행하는 엣지 AI에 대한 연구도 활발한데, 그 중 하나는 여러 IoT 장치들이 수집한 오디오 데이터를 활용하여, 다양한 AI 응용들을 IoT 엣지 컴퓨팅 환경에서 제공하는 것이다. 그러나, 이와 관련된 많은 연구에서, IoT 기기들은 에너지의 제약으로 인하여, 엣지 서버(IoT 서버)로의 센싱 데이터 전송만을 수행하고, 데이터 전처리를 포함한 모든 AI 과정은 엣지 서버에서 수행한다. 이 경우, 엣지 서버의 과부하 문제 뿐 아니라, 학습 및 추론에 불필요한 데이터까지도 서버에 그대로 전송되므로 네트워크 과부하 문제도 야기한다. 또한, 이를 해결하고자, 데이터 전처리 과정을 각 IoT 기기에 모두 맡긴다면, 기기의 에너지 부족으로 정전시간이 증가하는 또 다른 문제가 발생한다. 본 논문에서는 각 IoT 기기의 에너지 상태에 따라 데이터 전처리 여부를 결정함으로써, 기기들의 정전시간 증가 문제를 완화시키면서 서버 집중형 엣지 AI 환경의 문제들(엣지 서버 및 네트워크 과부하)을 완화시키고자 한다. 제안기법에서 IoT 장치는 기기가 기본적으로 동작하는 데 필요한 에너지 외의 여분의 에너지 양을 예측하고, 이 여분의 에너지가 있는 경우에만 이를 사용하여 기기에서 전처리 과정, 즉 수집 대상 소리 판별과 잡음 제거 과정을 거친 후 서버에 전송함으로써, IoT기기의 정전시간에 영향을 주지 않으면서, 에너지 적응적으로 데이터 전처리 위치(IoT기기 또는 엣지 서버)를 결정하여 수행한다.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.1-8
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• 2011

An underwater robot S/W framework consists of various sub-modules such as sensory data processing module, thruster control module, cognition module and behavior control module. Performance of a robot is determined by not only the efficiency of algorithms used but also effectiveness of their implementations. One most important factor of the effective implementation is the efficiency of data sharing module, as it transmits signals and data between the sub-modules and thus is directly related to the cycles of sensing and control The ideal data sharing module enables immediate access to any data source irrespective of system configurations. In reality, however, there are lots of obstacles including limitation of processing capacity of source modules, delay over network, and scheduling latency of operating systems. The paper proposes a new data sharing architecture and programming models to effectively handle such obstacles in implementation of underwater S/W framework on a small scale distributed computing system.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.1004-1010
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• 2019

In the EH-WSN (Energy harvesting wireless sensor network), a MAC (medium access control) protocol is required to select a relay node considering the power status of a node. Existing EH-WSN studies emphasize the power aspect, so it does not consider the QoS like the urgency of the sensed data. The required power and transmission delay must be changed according to the urgency so that the medium access control according to the data QoS can be performed. In case of relay node, relaying data without consideration of data urgency and node power may cause delay due to power shortage in case of urgent data. In this paper, we designed a MAC protocol that minimizes the power shortage that can occur during emergency data generation. For this, relay node requirements are set differently according to the urgency of data. The performance was analyzed through simulation. Simulation results show the reduced latency and improved reliability of urgent data transmission.

• Journal of KIISE:Information Networking
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• v.36 no.5
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• pp.413-424
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• 2009

Wireless sensor network is based on an event driven system. Sensor nodes collect the events in surrounding environment and the sensing data are relayed into a sink node. In particular, when events are detected, the data sensing periods are likely to be shorter to get the more correct information. However, this operation causes the traffic congestion on the sensor nodes located in a routing path. Since the traffic congestion generates the data queue overflows in sensor nodes, the important information about events could be missed. In addition, since the battery energy of sensor nodes exhausts quickly for treating the traffic congestion, the entire lifetime of wireless sensor networks would be abbreviated. In this paper, a new congestion control method is proposed on the basis of genetic algorithm. To apply genetic algorithm, the data traffic rate of each sensor node is utilized as a chromosome structure. The fitness function of genetic algorithm is designed from both the average and the standard deviation of the traffic rates of sensor nodes. Based on dominant gene sets, the proposed method selects the optimal data forwarding sensor nodes for relieving the traffic congestion. In experiments, when compared with other methods to handle the traffic congestion, the proposed method shows the efficient data transmissions due to much less queue overflows and supports the fair data transmission between all sensor nodes as possible. This result not only enhances the reliability of data transmission but also distributes the energy consumptions across the network. It contributes directly to the extension of total lifetime of wireless sensor networks.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.97-106
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• 2012

Management of biosignal data in mobile devices causes many problems in real-time transmission of large volume of multimedia data or storage devices. Therefore, this research paper intends to suggest an m-Health system, a clinical data processing system using mobile in order to provide quick medical service. This system deployed health system on IP network, compounded outputs from many bio sensing in remote sites and performed integrated data processing electronically on various bio sensors. The m-health system measures and monitors various biosignals and sends them to data servers of remote hospitals. It is an Android-based mobile application which patients and their family and medical staff can use anywhere anytime. Medical staff access patient data from hospital data servers and provide feedback on medical diagnosis and prescription to patients or users. Video stream for patient monitoring uses a scalable transcoding technique to decides data size appropriate for network traffic and sends video stream, remarkably reducing loads of mobile systems and networks.

• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.159-169
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• 2016

The current railway control system in Korea is comprised of signaling, electric rail power, communication, and maintenance systems that are independent of each other. Further, these systems have different mediums and protocols for transmitting the field equipment data to the central control system. The Safety Supervision System has as its purpose the collecting of safety-related data from each system to predict and prevent accidents, this system utilizes standard protocol. Safety-related data need to be collected from field data transmission devices of the existing control system, the data should be collected without affecting the communication of the existing system. In this study, sniffing skill, which is typically used for network traffic monitoring or security, is used to collect data. The problems arising from the use of sniffing devices are noted, and the Packet Conversion Node is proposed as a solution to the problems. Further, functional and performance testing were completed for the prototype, and the software architecture and packet conversion process were verified.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.21-27
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• 2022

As society develops and becomes more complex, new and diverse types of disasters such as fine dust and infectious diseases are occurring. However, in the past, there was no PA(Public Address) system that provided accurate information to prepare for such a disaster. In this paper, we propose a public address system that automatically broadcasts an alarm by analyzing polluted air quality data collected from public data and IoT sensors. The warning level varies depending on the air quality, and the information provided by public data may show a significantly different result from the guide area due to various factors such as the distance from the measuring station or the wind direction. To compensate for this, we are going to propose a method for broadcasting by comparing and analyzing data obtained from public data and data from on-site IoT sensors.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.478-480
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• 2005

센서 네트워크는 다수의 센서 노드들이 센싱된 데이터를 보고하는 형태의 네트워크로 기존 데이터 중심(Data-centric) 통신 모델은 오버헤드와 응답 속도의 저하와 관련된 문제점을 노출하고 있으며, 이를 해결하기 위한 방안으로 속성 기반 네이밍(Attribute-based naming)이 새로운 라우팅 구조로 주목받고 있다. 본 연구에서는 가상 대응체 (Virtual Counterpart) 개념을 센서 네트워크에 적용하여 속성 기반 네이밍을 싱크 노드내의 가상 센서 노드에서 처리해주는 구조를 제안하였다. 기존의 다른 속성 기반 네이밍 연구들과 달리 리얼센서에 대응되는 가상 센서 노드를 싱크 노드에서 운용하고, 리얼 센서의 데이터를 주기적으로 업데이트한 후, 속성 기반 쿼리를 가상 센서 노드가 리얼 센서를 대행하여 처리하는 구조를 설계하였다. 이런 구조를 취함으로써 효율적인 응답 처리와 하부 네트워크에 비종속적인 속성 기반 네이밍이 가능하며, 쿼리의 확장성과 센서들의 결합을 통한 부가적인 기능을 제공할 수 있게 된다.