• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.6
• /
• pp.909-917
• /
• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.2
• /
• pp.353-360
• /
• 2017

The Internet of Things(IoT) security has more need than a technical problem as it needs series of regulations and faultless security system for common purposes. So, this study proposes an efficient key management in order that can be trusted IoT data in cloud computing. In contrast with a key distribution center of existing sensor networks, the proposed a federation key management of cloud proxy key server is not central point of administration and enables an active key recovery and update. The proposed key management is not a method of predetermined secret keys but sharing key information of a cloud proxy key server in autonomous cloud, which can reduce key generation and space complexity. In addition, In contrast with previous IoT key researches, a federation key of cloud proxy key server provides an extraction ability from meaningful information while moving data.

• KNOM Review
• /
• v.23 no.1
• /
• pp.51-62
• /
• 2020

Open IoT platform that shares communication infrastructure and provides cloud resources can flexibly reduce development period and cost of smart service. In this paper, as an open IoT platform, we propose a virtual IoT system based on edge computing that implements a virtual IoT device for a physical IoT device and allows service developers to interact with the virtual device. A management server in the edge cloud, near the IoT physical device, manages the creation, movement, and removal of virtual IoT devices corresponding to the physical IoT devices. This paper define the operations of the management server, the physical IoT device, and the virtual IoT device, which are major components of the virtual IoT system, and design the communication protocol required to perform the operations. Finally, through simulations, this paper evaluate the performance of the edge computing based virtual IoT system by confirming that each component performs the defined states and operations as designed.

• Journal of Digital Convergence
• /
• v.19 no.4
• /
• pp.151-157
• /
• 2021

Recently, IoT technology has been applied to various cloud environments, requiring accurate verification of various information generated by IoT devices. However, due to the convergence of IoT technologies and 5G technologies, accurate analysis is required as IoT information processing is rapidly processed. This paper proposes a blockchain-based multi-IoT verification model for overlay cloud environments. The proposed model multi-processes IoT information by further classifying IoT information two layers (layer and layer) into bits' blockchain to minimize the bottleneck of overlay networks while ensuring the integrity of information sent and received from embedded IoT devices within local IoT groups. Furthermore, the proposed model allows the layer to contain the weight information, allowing IoT information to be easily processed by the server. In particular, transmission and reception information between IoT devices facilitates server access by distributing IoT information from bits into blockchain to minimize bottlenecks in overlay networks and then weighting IoT information.

• International Journal of Advanced Culture Technology
• /
• v.5 no.2
• /
• pp.90-97
• /
• 2017

The Internet of Things(IoT) market is expected to grow from 15.5billion to 75.4 billion by 2015-2025. As the number of IoT devices increases, the amount of data that is sent to the cloud is increasing. Today's Cloud Computing models are not suited to handle the vast amount of data generated by IoT devices. In this paper, we propose a Cooperation Coordinator System that reduces server load and improved real-time processing capability under specific circumstances by using Band-Cloud. The cooperation coordinator system dynamically forms the cloud when cooperation is needed between mobile devices located near. It is called Band-Cloud. Band-Cloud provides services entrusted by Central Cloud. This paper describes the proposed system and shows the cooperation process using the Android-based mobile devices and Wi-Fi Direct technology. Such a system can be applied to cases where real-time processing is required in a narrow area such as a hospital ward or a school classroom.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.2
• /
• pp.258-264
• /
• 2022

The smart farm for livestock, in which information and communication technology (ICT) is combined with livestock farm, is mostly based on the cloud computing paradigm. A cloud-based smart livestock farm has disadvantages such as increased response time, burden on cloud resource caused by the increased number of IoT sensors, traffic burden on the network, and lack of failure resilience mechanisms through collaboration with adjacent IoT devices. In this paper, with these problems in mind, we propose an IoT collaboration system based on edge computing. By using the relatively limited computing resources of the edge device to share the cloud's web server function, we aim to reduce the cloud's resources needed and improve response time to user requests. In addition, through the heartbeat-based failure recovery mechanism, IoT device failures were detected and appropriate measures were taken.

• Journal of Convergence for Information Technology
• /
• v.12 no.2
• /
• pp.23-29
• /
• 2022

Recently, due to the increase in the use of Internet of Things (IoT) devices, the amount of data transmitted and processed to cloud computing servers has increased rapidly. As a result, network problems (delay, server overload and security threats) are emerging. In particular, edge computing with lower computational capabilities than cloud computing requires a lightweight authentication algorithm that can easily authenticate numerous IoT devices.In this paper, we proposed a key-agreement protocol of a lightweight algorithm that guarantees anonymity and forward and backward secrecy between IoT and edge devices. and the proposed algorithm is stable in MITM and replay attacks for edge device and IoT. As a result of comparing and analyzing the proposed key-agreement protocol with previous studies, it was shown that a lightweight protocol that can be efficiently used in IoT and edge devices.

• Journal of Internet Computing and Services
• /
• v.19 no.1
• /
• pp.37-47
• /
• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.34 no.5
• /
• pp.301-308
• /
• 2021

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.4
• /
• pp.159-164
• /
• 2023

Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.