• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.1011-1012
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• 2016

최근 무선 통신 기술과 센서 디바이스들의 발달로 센서 기반 IoT 환경이 다양한 분야에 활용되고 있다. 하지만, IoT 환경을 구성하는 센서 노드가 소형 하드웨어로 구성되어 있어 메모리, 처리능력, 에너지 등에서 많은 제약사항을 가지고 있다. 따라서, 본 논문에서는 키 없는 해시 함수를 이용하여 센서 노드간 인증 및 키 교환을 경량화 기법을 제안한다. 제안하는 시스템은 숲이나 군사지역 등 사람이 접근하기 어려운 곳에 활용되는 센서 노드들의 배터리 수명을 향상시켜 효율적이고 지속적인 데이터 수집이 가능할 것으로 기대된다.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.513-520
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• 2016

As IoT devices become more common in the public sphere, the energy efficiency of embedded systems becomes a problem of major interest in addition to the system performance. Energy efficiency is important for portable embedded systems because they obtain power from their battery, and a low energy efficiency will result in a low usage time while a high energy efficiency will allow for longer usage time. In this paper, we propose a memory usage based frequency selection method to improve the energy efficiency of embedded Linux systems by using devfreq to select the device's system frequency. In our experiments, we found that the proposed method reduces energy consumption in an embedded device by up to 18%.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.47-52
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• 2023

With the growing data size and the increased computing load in machine learning, energy-efficient resource planning in IoT systems is becoming increasingly important. In this paper, we suggest a new resource planning policy for real-time workloads that can be fluctuated over time in IoT systems. To handle such situations, we categorize real-time tasks into fixed tasks and variable tasks, and optimize the resource planning for various workload conditions. Based on this, we initiate the IoT system with the configuration for the fixed tasks, and when variable tasks are activated, we update the resource planning promptly for the situation. Simulation experiments show that the proposed policy saves the processor and memory energy significantly.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.385-392
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• 2015

In IoT(Internet of Things), it is important for wireless networks to communicate data created among resource-constrained wireless nodes, where time synchronization is needed for meaningful data creation and transmission. Time Synchronization by flooding is one of the mostly used protocols for WSN(Wireless Sensor Networks). Even though this type of scheme has some advantages over other types (i.e. a simple algorithm and independency of topology and so on), too many data transmission is required, leading to large power consumption. So, reducing transmission data is an important issue for energy efficiency in this kind of networks. In this paper, a new Flooding-based time synchronization protocol is proposed to use energy efficiently by reducing a transmitted traffic. The proposed scheme's performance has been evaluated and compared with an representative scheme, FTSP(Flooding Time Synchronization Protocol) by simulation. The results are shown that the proposed scheme is better than FTSP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.602-608
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• 2020

Development of Internet technology and the spread of various smart devices provide a convenient computing environment for people, which is becoming common thanks to the Internet of Things (IoT). However, attacks by hackers have caused various problems, such as leaking personal information or violating privacy. In the IoT environment, various smart devices are connected, and network attacks that are used in the PC environment are occurring frequently in the IoT. In fact, security incidents such as conducting DDoS attacks by hacking IP cameras, leaking personal information, and monitoring unspecified numbers of personal files without consent are occurring. Although attacks in the existing Internet environment are PC-oriented, we can now confirm that smart devices such as IP cameras and tablets can be targets of network attacks. Through performance evaluation, the proposed protocol shows 11% more energy efficiency on servers than RSA, eight times greater energy efficiency on clients than Kerberos, and increased efficiency as the number of devices increases. In addition, it is possible to respond to a variety of security threats that might occur against the network. It is expected that efficient operations will be possible if the proposed protocol is applied to the IoT environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.273-281
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• 2019

The energy consumed by buildings among the total national energy consumption is more than 10% of the total. For this reason, Korea has adopted the zero energy building policy since 2025, and research on the energy saving technology of buildings has been demanded. Analysis of buildings' energy consumption patterns shows that lighting, heating and cooling energy account for more than 60% of total energy consumption, which is directly related to solar power acquisition and window opening and closing operation. In this paper, we have developed a low - power IoT sensor module for window system to transfer acquired information to building energy management system. This module transmits the external environment and window opening / closing status information to the building energy management system in real time, and constructs the network to actively take energy saving measures. The power used in the module is designed as an independent power source using solar power among the harvest energy. The topology of the power supply is a Buck converter, which is charged at 4V to the lithium ion battery through MPPT control, and the efficiency is about 85.87%. Communication is configured to be able to transmit in real time by applying WiFi. In order to reduce the power consumption of the module, we analyzed the hardware and software aspects and implemented a low power IoT sensor module.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.458-460
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• 2019

최근 클라우드 시스템 환경이 점차 늘어남에 따라 데이터 센터(IDC) 구축이 점차 늘어나가고 있다. 데이터 센터는 최근 부각하고 있는 4 차 산업 영역에서 사물 인터넷(IoT), 자율주행차 등 에서 처리될 대용량 데이터로 인한 이를 처리하는 중요한 역할을 담당하고 있다. 데이터센터 운영에는 대량의 에너지가 필요하다. 수 많은 컴퓨터에서 발생하는 열에너지를 처리하기 위하여 대량의 전력 냉방 에너지를 소비하고 있다. 냉방 공조 운영은 데이터 센터 운영에 중요한 역할을 한다. 이유는 많은 컴퓨터를 가동하는 비용보다 부대 시설로 운영되는 냉방 에너지를 보다 많이 소비하는 현상까지 발생하고 있다. 이에 최근 데이터 센터 냉방 공조 운영을 효율화하는 것에 연구를 맞추고 있다. 본 논문에서는 냉방 공조 운영 효율화 하도록 하기 위해서 다중 기계 학습을 활용한 데이터 센터의 냉방 에너지 절감 시스템을 제안하고자 한다. 기존의 단수 알고리즘을 활용하여 머신 러닝의 모델구현 방식이 아닌 다중의 기계 학습을 통하여 최적화된 모델을 일일 배치로 생성하여 예측을 하는 시스템이다. 본 시스템을 통하여 사전에 최적화된 냉방 운영을 하여 기존 데이터 센터의 운영되는 과다 냉방을 감축 시켜 에너지를 절감해주는 기능을 제공한다. 본 논문 시스템 연구 결과는 폭발적으로 늘어가고 있는 데이터 센터의 에너지 효율화에 기여할 수 있고, 클라우드 사업에서 경쟁력을 줄 수 있는 운영 시스템 방안을 제시한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.76-82
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• 2019

The development of Internet technology and the deployment of smart devices provide a convenient environment for people, and this is becoming common with the technology called the Internet of Things (IoT). But the development of, and demand for, IoT technology is causing various problems, such as personal information leaks due to the attacks of hackers who exploit it. A number of devices are connected to a network, and network attacks that have been exploited in the existing PC environment are occurring in the IoT environment. When it comes to IP cameras, security incidents (such as distributed denial of service [DDoS] attacks, hacking someone's personal information, and monitoring without consent) are occurring. However, it is difficult to install and implement existing security solutions because memory space and power are limited owing to the characteristics of small devices in the IoT environment. Therefore, this paper proposes a security protocol that can look at and prevent IoT security threats. A security assessment verified that the proposed protocol is able to respond to various security threats that could arise in a network. Therefore, it is expected that efficient operation of this protocol will be possible if it is applied to the IoT environment.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.17-23
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• 2016

In the future network such as Internet of Things (IoT), the number of computing devices are expected to grow exponentially, and each of the things communicates with the others and acquires information by itself. Due to the growing interest in IoT applications, the broadcasting in Opportunistic ad-hoc networks such as Machine-to-Machine (M2M) is very important transmission strategy which allows fast data dissemination. In distributed networks for IoT, the energy efficiency of the nodes is a key factor in the network performance. In this paper, we propose a fuzzy logic based probabilistic multi-hop broadcast (FPMCAST) algorithm which statistically disseminates data accordingly to the remaining energy rate, the replication density rate of sending node, and the distance rate between sending and receiving nodes. In proposed FPMCAST, the inference engine is based the fuzzy rule base which is consists of 27 if-then rules. It maps input and output parameters to membership functions of input and output. The output of fuzzy system defines the fuzzy sets for rebroadcasting probability, and defuzzification is used to extract a numeric result from the fuzzy set. Here Center of Gravity (COG) method is used to defuzzify the fuzzy set. Then, the performance of FPMCAST is evaluated through a simulation study. From the simulation, we demonstrate that the proposed FPMCAST algorithm significantly outperforms flooding and gossiping algorithms. Specially, the FPMCAST algorithm has longer network lifetime because the residual energy of each node consumes evenly.