• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.445-466
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• 2022

As everything linking to the internet, people can subscribe to various services from a service provider to facilitate their lives through the Internet of Things (IoT). An obligatory thing for the service provider is that they should push the service data safely and timely to multiple IoT terminal devices regularly after the IoT devices accomplishing the service subscription. In order to control the service message received by the legal devices as while as keep the confidentiality of the data, the public key encryption algorithm is utilized. While the existing public encryption algorithms for push service are too complicated for IoT devices, and almost of the current subscription schemes based on push mode are relying on centralized organization which may suffer from centralized entity corruption or single point of failure. To address these issues, we design a secure subscription-push service scheme based on blockchain and edge computing in this article, which is decentralized with secure architecture for the subscription and push of service. Furthermore, inspired by broadcast encryption and multicast encryption, a new encryption algorithm is designed to manage the permissions of IoT devices together with smart contract, and to protect the confidentiality of push messages, which is suitable for IoT devices. The edge computing nodes, in the new system architecture, maintain the blockchain to ensure the impartiality and traceability of service subscriptions and push messages, meanwhile undertake some calculations for IoT devices with limited computing power. The legalities of subscription services are guaranteed by verifying subscription tags on the smart contract. Lastly, the analysis indicates that the scheme is reliable, and the proposed encryption algorithm is safe and efficient.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.9-16
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• 2015

On modern operating systems such as Linux, virtual memory is a general way to provide a large address space to applications by using main memory and storage devices. Recently, storage devices have been improved in terms of latency and bandwidth, and it is expected that applications with large memory show high-performance if next-generation storage devices are considered. However, due to the overhead of virtual memory subsystem, the paging system can not exploit the performance of next-generation storage devices. In this study, we propose several optimization techniques to extend memory with next-generation storage devices. The techniques are to allocate block addresses of storage devices for write-back operations as well as to configure the system parameters, and we implement the techniques on Linux 3.14.3. Our evaluation through using multiple benchmarks shows that our system has 3 times (/24%) better performance on average than the baseline system in the micro(/macro)-benchmark.

• Journal of Information Technology Services
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• v.13 no.1
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• pp.125-134
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• 2014

Device discovery for D2D (device-to-device) communication enables a device to discover other devices in order to initiate communication with them. Devices should perform the discovery phase using a small quantity of radio resource in a short time and be able to reduce the load of the base station. Legacy device discovery schemes have focused on discovering as many target devices as possible. However, it is not appropriate for peer-to-peer D2D communication scenario. Further, synchronization problems are an important issue for discovery signal transmission. This paper proposes a discovery method that one requesting device discovers a specific target for communication. Multiple antenna beamforming is employed for the synchronization between the base station and a target device. The proposal can reduce the load of the base station using the information that it already maintains and improve the reliability of the device discovery because two times of synchronizations using beamforming among the base station and devices can make the exact discovery of a target device with mobility possible.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.148-167
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• 2020

Today, digital shoppers express increasingly complex buying behavior. They can use multiple channels for shopping and also they can switch from one to another channel almost effortlessly, in the result of engaging in omnichannel shopping behavior. A few years ago, consumers were using brick and mortar stores to make their purchases. However, nowadays, they possess different digital devices (mobile and/or desktop) to search for different alternatives and to make a better shopping choice. These devices (mobile and desktop) are different and offer unique benefits to consumers. However, there has been very little research that has treated mobile and desktop devices separately. Perhaps this study is the pioneer when it comes to investigating the effect of regulatory focus (prevention vs. promotion) and chronotype (morning and evening person) on a sample of university students using desktop and mobile channels for their shopping. The findings from a sample of 312 digital consumers (mobile and/or desktop) confirmed that the desktop channel provides a greater fit for morning-type respondents and that the mobile channel offers better value for evening-type respondents in e-retail. Furthermore, promotion-focused shoppers favor the mobile channel, and prevention-focused shoppers favor the desktop channel. The new insights and contributions of this study provide a better understanding of digital consumers to help sellers to develop a more effective e-retail strategy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.950-953
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd.

• Macromolecular Research
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• v.17 no.3
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• pp.192-196
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• 2009

Recently, the multi-screening of target materials has been made possible by the development of the surface plasmon resonance (SPR) imaging method. To adapt this method to biochemical analysis, the multi-patterning technology of protein microarrays is required. Among the different methods of fabricating protein microarrays, the microfluidic platform was selected due to its various advantages over other techniques. Microfluidic devices were designed and fabricated with polydimethylsiloxane (PDMS) by the replica molding method. These devices were designed to operate using only capillary force, without the need for additional flow control equipment. With these devices, multiple protein-patterned sensor surfaces were made, to support the two-dimensional detection of various protein-protein interactions with SPR. The fabrication technique of protein microarrays can be applied not only to SPR imaging, but also to other biochemical analyses.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.9-15
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• 2021

Recently, it is increasingly necessary to run high-end neural network applications with huge computation overhead on top of resource-constrained embedded systems, such as wearable devices. While the huge computational overhead can be alleviated by distributed neural networks running on multiple separate devices, existing distributed neural network techniques suffer from a large traffic between the devices; thus are very vulnerable to communication failures. These drawbacks make the distributed neural network techniques inapplicable to wearable devices, which are connected with each other through unstable and low data rate communication medium like human body communication. Therefore, in this paper, we propose a distributed neural network partitioning technique that is resilient to communication failures. Furthermore, we show that the proposed technique also improves the inference accuracy even in case of no communication failure, thanks to the improved network partitioning. We verify through comparative experiments with a real-life neural network application that the proposed technique outperforms the existing state-of-the-art distributed neural network technique in terms of accuracy and resiliency to communication failures.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.803-808
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• 2023

The IoT industry is growing at a record growth rate every year, but developers face practical problems such as security, data storage, and heterogeneity between devices before developing an IoT platform. In particular, heterogeneity between devices occurs due to network type and protocol, and device firmware must be changed or multiple IoT platforms must be used in some cases. In addition, data is wasted due to redundant sensing due to the overflow of indiscriminate IoT devices. In this paper, we propose a device-independent firmware design to solve the heterogeneity between devices in the IoT platform environment where Local WAS uses the MQTT protocol.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.191-196
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• 2024

Recently, research on intelligent IoT technology has been actively conducted by various companies and research institutes to analyze various data collected from IoT devices and provide it through actual application services. However, security issues such as personal information leakage may arise in the process of transmitting and receiving data to use data collected from IoT devices for research and development. In addition, as data collected from multiple IoT devices increases, data management difficulties exist, and data movement is costly and time consuming. Therefore, in this paper, we intend to develop an Ethereum network-based federated learning system with guaranteed reliability to improve security issues and inefficiencies in a federated learning environment composed of various devices.