• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.187-202
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• 2012

As a representative reuse paradigm, the theme of service-oriented Paradigm (SOC) is largely centered on publishing and subscribing reusable services. Here, SOC is the term including service oriented architecture and cloud computing. Service providers can produce high profits with reusable services, and service consumers can develop their applications with less time and effort by reusing the services. Design Patterns (DP) is a set of reusable methods to resolve commonly occurring design problems and to provide design structures to deal with the problems by following open/close princples. However, since DPs are mainly proposed for building object-oriented systems and there are distinguishable differences between object-oriented paradigm and SOC, it is challenging to apply the DPs to SOC design problems. Hence, DPs need to be customized by considering the two aspects; for service providers to design services which are highly reusable and reflect their unique characteristics and for service consumers to develop their target applications by reusing and customizing services as soon as possible. Therefore, we propose a set of DPs that are customized to SOC. With the proposed DPs, we believe that service provider can effectively develop highly reusable services, and service consumers can efficiently adapt services for their applications.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1129-1139
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• 2015

Inference process generates additional triples from knowledge represented in RDF triples of semantic web technology. Tens of million of triples as an initial big data and the additionally inferred triples become a knowledge base for applications such as QA(question&answer) system. The inference engine requires more computing resources to process the triples generated while inferencing. The additional computing resources supplied by underlying resource pool in cloud computing can shorten the execution time. This paper addresses an algorithm to allocate the number of computing nodes "elastically" at runtime on Hadoop, depending on the size of knowledge data fed. The model proposed in this paper is composed of the layered architecture: the top layer for applications, the middle layer for distributed parallel inference engine to process the triples, and lower layer for elastic Hadoop and server visualization. System algorithms and test data are analyzed and discussed in this paper. The model hast the benefit that rich legacy Hadoop applications can be run faster on this system without any modification.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.1-6
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• 2018

In smart cities, data from various kinds of sensors are collected and processed to provide smart services to the citizens. Noise information services with noise maps using the collected sensor data from various kinds of ubiquitous sensor networks is one of them. This paper presents a research result which generates three dimensional (3D) noise maps in real-time for smart cities. To make a noise map, we have to converge many informal data which include big image data of geographical Information and massive sensor data. Making such a 3D noise map in real-time requires the processing of the stream data from the ubiquitous sensor networks in real-time and the convergence operation in real-time. They are very challenging works. We developed our own methodology for real-time distributed and parallel processing for it and present it in this paper. Further, we developed our own real-time 3D noise map generation system, with the methodology. The system uses open source softwares for it. Here in this paper, we do introduce one of our systems which uses Apache Storm. We did performance evaluation using the developed system. Cloud computing was used for the performance evaluation experiments. It was confirmed that our system was working properly with good performance and the system can produce the 3D noise maps in real-time. The performance evaluation results are given in this paper, as well.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1666-1672
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• 2016

In recent years, smart technology has been applied to various information system fields. Especially, traditional library service area is changing to Smart-Library from Digital-Library. In this environment are need to library service software platform for supporting variety content, library services, users and smart-devices. Due to this, existing library service has a limitation that inhibits semantic interoperability between different heterogeneous library systems. In this paper, we propose Linked-Open-Data based smart library as an archetype of future-library system that provide a variety content and system interaction and integration of services. It is an innovative system of the cutting-edge information intensive. Therefore, we designed system environments according to various integration requirements for smart library based on Linked-Open-Data. And, we describe the functional requirements of smart-library systems by considering the users' demands and the eco-systems of information technology. In addition, we show the reference framework, which can accommodate the functional requirements and provide smart knowledge service to user through a variety of smart-devices.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.178-185
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• 2018

Recently, demands for computer systems with multicore CPUs and high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in cloud computing, surer-computing, and enterprise storage/database systems. Journaling file systems running on high-performance systems do not exploit the full I/O bandwidth of high-performance SSDs. In this article, we evaluate and analyze the performance of the Linux EXT4 file system with high-performance SSDs and multicore CPUs. The system used in this study has 72 cores and Intel NVMe SSD, and the flash SSD has performance up to 2800/1900 MB/s for sequential read/write operations. Our experimental results show that checkpointing in the EXT4 file system is a major overhead. Furthermore, we optimize the checkpointing procedure and our optimized EXT4 file system shows up to 92% better performance than the original EXT4 file system.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.601-613
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• 2016

With the increasing need for big data processing, building a shared big data processing platform is important to minimize time and monetary costs. In shared big data processing, multitenancy is a major requirement that needs to be addressed, in order to provide a single isolated personal big data platform for each user, but to share the underlying hardware is shared among users to increase hardware utilization. In this paper, we explore two well-known shared big data processing platform models. One is to use a native Hadoop cluster, and the other is to build a virtual Hadoop cluster for each user. For each model we verified whether it is sufficient to support multi-tenancy. We also present a method to complement unsupported multi-tenancy features in a native Hadoop cluster model. Lastly we built prototype platforms and compared the performance of both models.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.129-137
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• 2018

NVMe(Non-Volatile Memory Express) SSD(Solid State Drive) is a high-performance storage that makes use of flash memory as a storage cell, PCIe as an interface and NVMe as a protocol on the interface. It supports multiple I/O queues which makes it feasible to process parallel-I/Os on multi-core environments and to provide higher bandwidth than SATA SSDs. Hence, NVMe SSD is considered as a next generation-storage for data-center and cloud computing system. However, in the virtualization system, the performance of NVMe SSD is not fully utilized due to the bottleneck of the software I/O stack. Especially, when it uses I/O stack of the hypervisor or the host operating system like Xen and KVM, I/O performance degrades seriously due to doubled-I/O stack between host and virtual machine. In this paper, we propose a new I/O engine, called Direct-AIO (Direct-Asynchronous I/O) engine, that can access NVMe SSD directly for I/O performance improvements on QEMU emulator. We develop our proposed I/O engine and analyze I/O performance differences between the existed I/O engine and Direct-AIO engine.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.19-28
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• 2012

Recently a grid and cloud computing collaboration have become a social issue. These collaborative network system, the P2P system based on this system. Distingui shed from the client/server systems, P2P systems in order to exchange information, its purpose and functions are divided according to the morphological Category. In accordance with the purposes and functions of information and data retrieval, remote program control and integration services for the offers. Most P2P systems client/server scalability, and management takes the form, but to overcome the disadvantages in terms of applying the mixed-mode system is increasing. And recently the distributed computing aspects of the service to users in order to provide suitable to accommodate the diverse needs of various types of mobile agent technology is needed. In this paper, as required by the mobile agent access to a remote resource access control and agent for the execution and management capabilities and improve the reliability of the mobile agent system designed to suggest.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.1-7
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• 2015

As recent smartphone is used around the world, all of the subscribers of the mobile communication is up to 47.7% about 24 million people. Smartphone has a vulnerability to security, and security-related incidents are increased in damage with the smartphone. However, precautions have been made, rather than analysis of the infection of most of the damage occurs after the damaged except for the case of the expert by way of conventional post-countermeasure. In this paper, we implement a mobile-based malware analysis systems apply a virtualization technology. It is designed to analyze the behavior through it. Virtualization is a technique that provides a logical resources to the guest by abstracting the physical characteristics of computing resources. The virtualization technology can improve the efficiency of resources by integrating with cloud computing services to servers, networks, storage, and computing resources to provide a flexible. In addition, we propose a system that can be prepared in advance to buy a security from a user perspective.