• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.236-240
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• 2008

People use diary or photograph for recall-ing their memory in order to satisfy their desires for recording their lives. If the experienced events are organized to a story, S/he can share her/his experience with others, and recall her/his significant events easily. In this paper, we propose a method that generates a story with Petri net and user contexts collected from mobile device. Here, we use Petri-net as a representation method that links human activities or experience causally. It is appropriate solution for modeling parallel events in real world, and for representing non-linear story line. In order to show the usefulness of the proposed method, we show an example of generating a story of user's experience with user contexts from mobile device and evaluate them.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.850-858
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• 2022

To deploy Gate Recurrent Units (GRU) on resource-constrained embedded devices, this paper presents a reconfigurable FPGA-based GRU accelerator that enables structured compression. Firstly, a dense GRU model is significantly reduced in size by hybrid quantization and structured top-k pruning. Secondly, the energy consumption on external memory access is greatly reduced by the proposed reuse computing pattern. Finally, the accelerator can handle a structured sparse model that benefits from the algorithm-hardware co-design workflows. Moreover, inference tasks can be flexibly performed using all functional dimensions, sequence length, and number of layers. Implemented on the Intel DE1-SoC FPGA, the proposed accelerator achieves 45.01 GOPs in a structured sparse GRU network without batching. Compared to the implementation of CPU and GPU, low-cost FPGA accelerator achieves 57 and 30x improvements in latency, 300 and 23.44x improvements in energy efficiency, respectively. Thus, the proposed accelerator is utilized as an early study of real-time embedded applications, demonstrating the potential for further development in the future.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.778-789
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• 2021

Recently, various lightweight methods for using Convolutional Neural Network(CNN) models in mobile devices have emerged. Weight quantization, which lowers bit precision of weights, is a lightweight method that enables a model to be used through integer calculation in a mobile environment where GPU acceleration is unable. Weight quantization has already been used in various models as a lightweight method to reduce computational complexity and model size with a small loss of accuracy. Considering the size of memory and computing speed as well as the storage size of the device and the limited network environment, this paper proposes a method of compressing integer weights after quantization using a video codec as a method. To verify the performance of the proposed method, experiments were conducted on VGG16, Resnet50, and Resnet18 models trained with ImageNet and Places365 datasets. As a result, loss of accuracy less than 2% and high compression efficiency were achieved in various models. In addition, as a result of comparison with similar compression methods, it was verified that the compression efficiency was more than doubled.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.461-470
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• 2016

As IoT is broadly used in many fields, the security of IoT is becoming especially important and critical issues. Security and privacy are the key issues for IoT applications, and still faced with some enormous challenges. Sensor has limited resources such as computing power, memory, battery. By means of deeply analyzing the security architecture and features in security framework. While a number of researchers have explored such security challenges and open problems in IoT, there is an unfortunate lack of a systematic study of the security challenges in the IoT landscape. This special issue features recent and emerging advances IoT architecture, protocols, services and applications. The alternative method is IoT security gateway. In this paper, we surveyed the demands and requirements. By means of deeply analyzing the security architecture and features, we analyzed the demands and requirements for security based on gateway application.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.87-97
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• 2023

Containers are an emerging virtualization technology that can build an isolated environment more lightweight and faster than existing virtual machines. For that reason, many organizations have recently adopted them for their services. Yet, the container architecture has also exposed many security problems since all containers share the same OS kernel. In this work, we focus on the fact that an attacker can abuse host resources to make them unavailable to benign containers-also known as host resource exhaustion attacks. Then, we analyze the impact of host resource exhaustion attacks through real attack scenarios exhausting critical host resources, such as CPU, memory, disk space, process ID, and sockets in Docker, the most popular container platform. We propose five attack scenarios performed in several different host environments and container images. The result shows that three of them put other containers in denial of service.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.903-910
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• 2024

Complex semantic segmentation tasks are primarily performed in server environments equipped with high-performance graphics hardware such as GPUs and TPUs. This cloud-based AI inference method operates by transmitting processed results to the client. However, this approach is dependent on network communication and raises concerns about privacy infringement during the process of transmitting user data to servers. Therefore, this paper proposes a Generalized On-Device Framework for Semantic Segmentation that can operate in mobile environments with high accessibility to people. This framework supports various semantic segmentation models and enables direct inference in mobile environments through model conversion and efficient memory management techniques. It is expected that this research approach will enable effective execution of semantic segmentation algorithms even in resource-constrained situations such as IoT devices, autonomous vehicles, and industrial robots, which are not cloud computing environments. This is expected to contribute to the advancement of real-time image processing, privacy protection, and network-independent AI application fields.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.5
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• pp.468-476
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• 2000

Binding the object-oriented programming language C++ with a database management system provides a persistency to C++ programming objects so that objects can persist after program termina~,on. In such a binding system, we can manage a persistent object same as that we use a transient object and also use database management facilities such as transaction management and concurrency control. This paper presents a method providing the persistency to C++ programming objects in the binding system. We propose an improved interface based on C++ binding of ODMG-97 and present the design and implementation technique of it. The proposed interface provides a seamless interface for creating objects of the persistent capable class. We can create a persistent object without its class name as we do not give a class name when creating a transient object. Also, we guarantee the type compatibilty between the obiect created in database and the obiect created in main memory.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.515-519
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• 2009

As the application fields of sensor nodes are getting diverse these days, it is required to have a way of collecting various data that is suitable for these application fields. In the case that the real-time surveillance over the data is unnecessary, present data collecting methods, which collect and transfer the data directly, can cause a waste of energy and data loss, A new method that store the collected data in a local storage and acquire them by query later on is required for nonreal-time applications. NAND flash has energy efficiency and large capacity so it is suitable for sensor nodes, Sensor nodes support 4-10 KBytes small sized memory and it is hard to build an effective file system since NAND Flash doesn't support overwriting NAND flash. This paper discusses an implementation of NAND Flash file system in sensor node environments. The file system makes long-term data collecting possible by reducing transmission cost. It is expected that this file system will play a central role in sensor network environments as it can be applied to various fields which call for long term data collecting.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.275-284
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• 2010

GPUs are stream processors based on multi-cores, which can process large data with a high speed and a large memory bandwidth. Furthermore, GPUs are less expensive than multi-core CPUs. Recently, usage of GPUs in general purpose computing has been wide spread. The CUDA architecture from Nvidia is one of efforts to help developers use GPUs in their application domains. In this paper, we propose techniques to parallelize a skyline algorithm which uses a simple nested loop structure. In order to employ the CUDA programming model, we apply our optimization techniques to make our skyline algorithm fit into the performance restrictions of the CUDA architecture. According to our experimental results, we improve the original skyline algorithm by 80% with our optimization techniques.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.359-366
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• 2003

Although the reuse of the cached data for scrolling the map reduces the amount of passed data between client and server, it needs the conversions of data coordinates, selective deletion of objects, cache compaction and object structuring step in the clients. The conversion is a time- intensive operation due to limited resources of mobile phones such as low computing power, small memory. Therefore, in order to control the map efficiently in the vector map service based mobile phones, it is necessary to study the methods which reuse cached objects for reducing wireless network bandwidth and overwhelming the limited resources of mobile phones as well. This paper proposes the methods of reusing pre-received spatial objects for map control in the mobile vector map service system based on client-server architecture. The experiments conducted on the Web GIS systems with real data show that the proposed method is appropriate to map services for mobile phone. We also analyze the advantages and drawbacks between the reuse of cached data and transmission of raw data respectively.