• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2527-2532
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• 2013

There coexist various access network for mobile terminals, such as mobile phones, smart phones, and tablet PC, in mobile and wireless network. In these circumstance, the network traffic overload unexpected causes the service degradation or discontinuity. To solve this problem, we consider a off-loading route selection by a cloud server which monitors traffic volume and selects an appropriate route. With our proposed scheme, it is possible for the EPC network with untrusted WLAN access networks to operate efficiently to a trusted service level. Also, an optimal handover with satisfying service requirements could be achieved by the proposed offload scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.603-606
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• 2013

Mobile and wireless communication technologies to the development of a variety of next-generation mobile networks such as smart phones, tablet PC and mobile terminals will coexist various access networks. In a variety of network service continuity and quality of service degradation due to network conditions, and the EPC network traffic overload phenomenon still remains a problem. In this paper, the EPC network traffic overload in distributed cloud servers is proposed to select. Our proposed scheme using an efficient network handover can provide optimal service according to the network condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.352-354
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• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In previous studies, sensor data was managed by distributed database system which built in a single server or a grid server. Thus, it has disadvantages such as low scalability, and high cost of building or managing the system. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.

• Smart Media Journal
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• v.12 no.11
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• pp.145-153
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• 2023

In a P2P-based distributed storage system where peers frequently join and leave, it is essential to guarantee not only data availability but also playback quality comparable to that provided by local storage devices when playing back video files with real-time constraints. In addition, cloud storage services based on distributed storage systems provide each user with the functionality to share their files with other users, so when multiple users request playback of the same video file at the same time, all playback should be supported seamlessly in real time. Therefore, in this paper, we propose a scheme that process multiple simultaneous playback requests for each video file in real time as well as data availability in a P2P-based distributed storage system that supports file sharing. This scheme can support real-time simultaneous playback and efficiently use storage space by adjusting the amount of redundant data encoded through erasure coding according to the number of concurrent playback requests for each video file.

• Journal of KIISE
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• v.44 no.8
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• pp.767-773
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• 2017

In a distributed system environment, such as a cloud database, the tail latency needs to be kept short to ensure uniform quality of service. In this paper, through experiments on a Cassandra database, we show that long tail latency is caused by a lack of memory space because the database cannot receive any request until free space is reclaimed by writing the buffered data to the storage device. We observed that, since the performance of the storage device determines the amount of time required for writing the buffered data, the performance degradation of Solid State Drive (SSD) due to garbage collection results in a longer tail latency. We propose a garbage collection synchronization technique, called SyncGC, that simultaneously performs garbage collection in the java virtual machine and in the garbage collection in SSD concurrently, thus hiding garbage collection overheads in the SSD. Our evaluations on real SSDs show that SyncGC reduces the tail latency of $99.9^{th}$ and, $99.9^{th}-percentile$ by 31% and 36%, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.8
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• pp.474-480
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• 2014

In this paper, we propose a study for the next generation terrestrial broadcasting technology based on SFN(Single Frequency Networks), which applies multiple receiving antenna to improve receiving performance of cloud transmission system. By applying multiple receiving antenna, the received broadcast signals at the boundary of different SFN broadcasting area could be modelled by distributed MIMO system. Due to the interference cancellation effect of the MIMO detector, the proposed scheme could suppress the adjacent area interference more efficiently compared to the single receiving antenna case. Simulation results show that receiving performance can be improved dramatically in overlapping area of SFN by applying multiple antenna receivers in cloud transmission system.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.9-17
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• 2017

The current study attempted to develop and operate an exercise prescription expert system based on cloud computing. Recently, concerns on health are increasing due to the development of healthcare technology, increased life expectancy, and enhanced concerns on the body figure and wellbeing among Koreans. This trend pushes up the demand for the personal trainers and exercise specialists. However, supply of the exercise specialists are less than the demand. This study tries to develop exercise prescription system, aggregate diverse data, develop artificial intelligence rule, and operate exercise prescription expert system and education system. This system may assist training exercise professionals by replacing off-line training programs into on-line training programs. Further researches are recommended to connect diverse IoT devices and big data.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.45-56
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• 2017

In astronomy, the amount of data generated using wide-field optical telescope has increased exponentially. However, the fixed-size small-scale computing environment and the complexity of data analysis tools, results in difficulties to process the massive observation data collected. To resolve this problem, we propose a cloud-based automation system for the efficient processing of the enormous data gathered. The proposed system consists of a Workflow Execution Manager which manages various workflow templates and controls the execution of workflows instantiated from theses templates, and an Elastic Resource Manager that dynamically adds/deletes computing resources, according to the amount of data analysis requests. To show the effectiveness of our proposed system, we exhaustively explored a board spectrum of experiments, like elastic resources allocation, system load, etc. Finally, we describe the best practice case of DEEP-SOUTH scheduling system as an example application.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.76-81
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• 2019

This paper is a review of the certification system required for various energy prosumer business models, including P2P energy trading and participation in small demand response programs, which are based on reliable production and consumption certification. One of the most important parameter in energy trading is ensuring the reliability of trading account balancing. Therefore, we studied to use big data pattern analysis based blockchain smart contract between trading partners to make its tradings are more reliable. For this purpose big data analysis system collected from the IoT AMI and a production authentication system using a private blockchain network linked with the AMI is discussed, using the blockchain smart contract are also suggested. Futhermore, energy trading system concept and business models are introduced.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.11-21
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• 2015

If the cloud computing environment is not sufficiently provide the required resources due to the number of virtual server to process the request, may cause a problem that the load applied to the specific server. Migration administrator receive the resources of each physical server for improving the efficiency of the virtual server that exists in the physical servers, and determines the migration destination based on the simulation results. But, there is more overhead predicting the future resource consumption of all the physical server to decide the migration destination through the simulation process in large and complex cloud computing environments. To solve this problem, we propose an improved prediction method with the simulation-based approach. The proposed method is a fuzzy-logic based priority model for VM migration. We design a proposed model with the DEVS formalism. And we also measure and compare a performance and migration count with existing simulation-based migration method. FPLM shows high utilization.