• Journal of Information Technology Applications and Management
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• v.29 no.1
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• pp.1-28
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• 2022

To realize the vision of internet of things (IoT), where it is expected to bring significant impact to the global economy in the future, consideration of business models in the IoT context is necessary. This research attempts to build an enhanced artifact business model framework based on the definitions of IoT and literature on business models for analysis of IoT businesses. The framework is used to analyze four different types of players: the owner of things, vendors of devices, providers of connectivity and providers of IoT application services. The findings suggest that the owners of things tend to partner with ICT players to complement their weakness, and it tends to be connectivity providers. The device vendors leverage their strength of devices and device platforms to attract and enable 3rd party sensor/devices to interconnect, while the service providers are aiming to penetrate into customer premise. These lead to the following recommendations for non-IT players to consider in expanding into IoT business: 1) take into account differences in product development process between IT and non-IT businesses in expanding into IoT market; 2) collaborate with ICT players that acknowledge and understand the differences.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.123-131
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• 2019

The Internet of Things (IoT) environment must be able to meet the needs of users by providing access to various services that can be used to develop diverse user applications. However, QoS issues arise due to the characteristics of the IoT environment, such as numerous heterogeneous devices and potential resource constraints. In this paper, we propose a QoS prediction method that reflects trust between users in SOA based IoT. In order to increase the accuracy of QoS prediction, we analyze the trust and distrust relations between users and identify similarities among users and predict QoS based on them. The centrality is calculated to enhance trust relationships. Experimental results show that QoS prediction can be improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.91-97
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• 2017

IoT (Internet of Things) systems are based on heterogeneous hardware systems of different types of devices interconnected each other, ranging from miniaturized and low-power wireless sensor node to cloud servers. These IoT systems composed of heterogeneous hardware utilize data sets collected from a particular set of sensors or control designated actuators when needed using open APIs created through abstraction of devices' resources associated to service applications. However, previously existing IoT services have been usually developed based on vertical platforms, whose sharing and exchange of data is limited within each industry domain, for example, healthcare. Such problem is called 'data silo', and considered one of crucial issues to be solved for the success of establishing IoT ecosystems. Also, IoT services may need to dynamically organize their services according to the change of status of connected devices due to their mobility and dynamic network connectivity. We propose a way of dynamically composing IoT services under the concept of WoT (Web of Things) where heterogeneous devices across different industries are fully integrated into the Web. Our approach allows developers to create IoT services or mash them up in an efficient way using Web objects registered into multiple standardized horizontal IoT platforms where their resources are discoverable and accessible. A Web-based service composition tool is developed to evaluate the practical feasibility of our approach under real-world service development.

• Journal of KIISE
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• v.43 no.4
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• pp.460-469
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• 2016

Internet of Things (IoT) is an environment where various devices are connected to each other via a wired/wireless network and where the devices gather, process, exchange, and share information. Some of the most important types of IoT devices are mobile IoT devices such as smartphones. These devices provide various high-performance services to users but cannot be supplied with power all the time; therefore, power management appropriate to a given IoT environment is necessary. Power management of mobile IoT devices involves complex relationships between various entities such as application processors (APs), HW modules inside/outside AP, Operating System (OS), platforms, and applications; a method is therefore needed to systematically analyze and manage these relationships. In addition, variabilities related to power management such as various policies, operational environments, and algorithms need to be analyzed and applied to power management development. In this paper, engineering principles and a method based on them are presented in order to address these challenges and support systematic development of IoT device power management. Power management of connected helmet systems was used to validate the feasibility of the proposed method.

• KNOM Review
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• v.22 no.2
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• pp.29-38
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• 2019

The rapid growth of IoT (Internet of Things) owing to the advancement and spread of technologies such as wireless networks, communication modules, sensors, smart terminals, etc. enables the development of new services in diverse public and private sectors. In particular, research on IoT technology and its applications has increased in the field of science. To establish an IoT infrastructure in this field, KREONET launched the wireless IoT network, called ScienceLoRa, based on low power wide area network (LPWAN). ScienceLoRa aims to collect a variety of data from sensors and utilize and analyze the collected data for research in a variety of scientific fields. In this article, the authors present the concept, current status, applications and future plans of ScienceLoRa.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.51-58
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• 2015

Internet of Thing is a collection of various technical components, and the interworking among heterogeneous devices, networks, applications is expected to be accelerated through the openness of IoT platform. For this reason, many technical and administrative security threats will occur in IoT environments. In this paper, authentication methods of recent researches are analyzed for safe IoT services, and new mutual authentication protocol is proposed to provide more secure communication. The proposed protocol prevents an impersonation as malicious gateway or illegal device providing mutual authentication between gateway and IoT device. The performance analysis and evaluation of proposed authentication protocol are performed.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.235-238
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• 2024

This paper investigates the integration of ARIA cryptography within hardware secure modules to bolster IoT security. We present a comparative analysis of two prominent IoT communication protocols, MQTT and LwM2M, augmented with ARIA cryptography. The study evaluates their performance, security, and scalability in practical IoT applications. Our experimental setup comprises FPGA-enabled hardware secure modules interfaced with Raspberry Pi acting as an MQTT and LwM2M client. We utilize the Mosquitto MQTT server and an LwM2M server deployed on AWS IoT. Through rigorous experimentation, we measure various performance metrics, including latency, throughput, and resource utilization. Additionally, security aspects are scrutinized, assessing the resilience of each protocol against common IoT security threats. Our findings highlight the efficacy of ARIA cryptography in bolstering IoT security and reveal insights into the comparative strengths and weaknesses of MQTT and LwM2M protocols. These results contribute to the development of robust and secure IoT systems, paving the way for future research in this domain.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.