• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1101-1113
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• 2021

The rapid growth of sense-and-respond applications and the emerging cloud computing model present a new challenge: providing publish/subscribe middleware as a scalable and elastic cloud service. The publish/subscribe interaction model is a promising solution for scalable data dissemination over wide-area networks. In addition, there have been some work on the publish/subscribe messaging paradigm that guarantees reliability and availability in the face of node and link failures. These publish/subscribe systems are commonly used in information-centric networks and edge-fog-cloud infrastructures for IoT. The IoT has an edge-fog cloud infrastructure to efficiently process massive amounts of sensing data collected from the surrounding environment. In this paper. we propose a quorum-based hierarchical fault-tolerant publish/subscribe systems (QHFPS) to enable reliable delivery of messages in the presence of link and node failures. The QHFPS efficiently distributes IoT messages to the publish/subscribe brokers in fog overlay layers on the basis of proposing extended stepped grid (xS-grid) quorum for providing tolerance when faced with node failures and network partitions. We evaluate the performance of QHFPS in three aspects: number of transmitted Pub/Sub messages, average subscription delay, and subscritpion delivery rate with an analytical model.

• ETRI Journal
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• v.44 no.4
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• pp.543-559
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• 2022

To determine a suitable waveform for Internet of Things (IoT) transmission over low-Earth orbit (LEO) satellites, this paper reports the results of a performance comparison between chirp spread spectrum (CSS)-based LoRa and direct sequence spread spectrum (DSSS)-based Ingenu. The performance of both waveforms was measured in terms of the packet error rate, throughput, and packet loss rate, considering the Doppler effect caused by the high speed of LEO satellites and the interference among multiple terminals. Simulation results indicate that the DSSS scheme is more suitable than the CSS scheme for high-traffic IoT services because of its robustness against interference among multiple terminals. However, the CSS scheme is more suitable than the DSSS scheme for high-mobility IoT services because of its robustness against the Doppler effect. We discuss various solutions, such as the preprocessing of Doppler effect and avoidance of packet collision, to enhance the performance of the DSSS and CSS schemes. The simulation results of the proposed solution show that the enhanced DSSS scheme can be a proper waveform in IoT transmission over LEO satellites for both the high-traffic and high-mobility services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1463-1469
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• 2020

Multimedia information, including video and voice, is highly utilized in that it is easily understood by people. For this reason, applications have been studied which store multimedia information in IoT devices and transmit information in conjunction with smartphones. The problem is that the size of information can be larger than the capacity of IoT devices due to video and image. In this paper, the multimedia content design technique, which takes into account the limitations of storage capacity, was studied when there is a limit of storage capacity. Considering that the video has a higher understanding of information than text, while the capacity is larger, the solution between information comprehension and capacity is sought. The size of static and dynamic media is a variable and the harm is solved in accordance with the linear planning method. Case studies have shown that the design techniques of this paper are useful.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.1-8
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• 2020

Water consumption has grown at more than 2.5 times, comparing the past century. About 2.8 billion people live in river basins with some form of water deficit, because more than 75 % of the river flows are withdrawn for agriculture and other needs. Challenges faced by more and more countries in their struggle for economic and social development are increasingly related to water. This paper proposes a test of an effective local river field environment management solution. And describing a part of a pilot project for the ministry of water resources of Uzbekistan. Current work focused on direct action items of the existing project and describe an IoT routing based solution for local river field environment management solutions. Suggested technological decisions provided by needs and on-site testing results. The paper describes the backbone of IoT routing based river water resources management system.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.198-204
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• 2019

In this study, the author introduces a supply-chain management (SCM) solution that connects suppliers, manufacturers, customers, and other companies within a transactional relationship to enable efficient inventory management and timely product supply, which ultimately maximizes corporate profits. This proposed solution exploits Fourth Industrial Revolution technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), which provide solutions to complex management issues generated by the broader market. The goal of the current study was to develop an advanced and intelligent smart SCM solution that complies with logistics standards, to enhance the visibility, safety, and efficiency of a supply chain made up of manufacturers and suppliers. This smart SCM solution aims at maximizing corporate profits through efficient inventory management and timely supply of products, and solves the complex management problems caused by operating within a wide range of markets.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.35-42
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• 2019

In this paper, we propose an approach to apply network-based moving target defense into Internet of Things (IoT) networks. The IoT is a technology that provides the high interconnectivity of things like electronic devices. However, cyber security risks are expected to increase as the interconnectivity of such devices increases. One recent study demonstrated a man-in-the-middle attack in the statically configured IoT network. In recent years, a new approach to cyber security, called the moving target defense, has emerged as a potential solution to the challenge of static systems. The approach continuously changes system's attack surface to prevent attacks. After analyzing IPv4 / IPv6-based moving target defense schemes and IoT network-related technologies, we present our approach in terms of addressing systems, address mutation techniques, communication models, network configuration, and node mobility. In addition, we summarize the direction of future research in relation to the proposed approach.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.1
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• pp.38-44
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• 2021

Wi-Fi provides some low-power connection solutions that other Bluetooth cannot provide, and at the same time brings many benefits. First, there is a potentially higher data rate: it can reach 230mbps. Wi-Fi coverage is also wider than competitors, and its operating frequency is also 5GHz, which is much less congested than 2.4GHz. Finally, it also supports IP networks, which is important if you want to send data to the cloud without complexity. The 802.11ac standard of the previous generation still accounts for most shipments (80.9%) and revenue (76.2%). However, there is a limit to accepting IoT devices that will continue to increase significantly in the future. To solve this problem, the new Wi-Fi 6 standard is expected to be the solution (IEEE 802.11ax) which is quickly becoming the main driving force of the wireless local area network (WLAN) market. According to IDC market research analysts, in the first quarter of 2020, independent access points (APs) supported by Wi-Fi 6 accounted for 11.8% of shipments, but 21.8% of revenue. In this paper, we have compared and analyzed the IoT connectivity, QoS, and security requirements of devices using Wi-Fi 6 network.

• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.