• Journal of Computing Science and Engineering
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• v.12 no.1
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• pp.24-35
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• 2018

Deep convolutional neural network (DCNN) is an advanced technology in image recognition. Because of extreme computing resource requirements, DCNN implementation with software alone cannot achieve real-time requirement. Therefore, the need to implement DCNN accelerator hardware is increasing. In this paper, we present a field programmable gate array (FPGA)-based hardware accelerator design of DCNN targeting handwritten Hangul character recognition application. Also, we present design optimization techniques in SDAccel environments for searching the optimal FPGA design space. The techniques we used include memory access optimization and computing unit parallelism, and data conversion. We achieved about 11.19 ms recognition time per character with Xilinx FPGA accelerator. Our design optimization was performed with Xilinx HLS and SDAccel environment targeting Kintex XCKU115 FPGA from Xilinx. Our design outperforms CPU in terms of energy efficiency (the number of samples per unit energy) by 5.88 times, and GPGPU in terms of energy efficiency by 5 times. We expect the research results will be an alternative to GPGPU solution for real-time applications, especially in data centers or server farms where energy consumption is a critical problem.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.491-496
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• 2015

Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.327-332
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• 2016

The routing protocol for low-power and lossy networks (RPL) is an internet protocol based routing protocol developed and standardized by IETF in 2012 to support a wide range of applications for low-power and lossy-networks (LLNs). In LLNs consisting of resource-constrained devices, the energy consumption of battery powered sensing devices during network operations can greatly impact network lifetime. In the case of inefficient route selection, the energy depletion from even a few nodes in the network can damage network integrity and reliability by creating holes in the network. In this paper, a composite energy-aware node metric ($RER_{BDI}$) is proposed for RPL; this metric uses both the residual energy ratio (RER) of the nodes and their battery discharge index. This composite metric helps avoid overburdening power depleted network nodes during packet routing from the source towards the destination oriented directed acyclic graph root node. Additionally, an objective function is defined for RPL, which combines the node metric $RER_{BDI}$ and the expected transmission count (ETX) link quality metric; this helps to improve the overall network packet delivery ratio. The COOJA simulator is used to evaluate the performance of the proposed scheme. The simulations show encouraging results for the proposed scheme in terms of network lifetime, packet delivery ratio and energy consumption, when compared to the most popular schemes for RPL like ETX, hop-count and RER.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.377-386
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• 2020

Mobile cloud computing involves mobile or embedded devices as clients, and features small devices with constrained resource and low availability. Due to the fast expansion of smart phones and smart peripheral devices, researches on mobile cloud computing attract academia's interest more than ever. Computation offloading, or code offloading, enhances the performance of computation by migrating a part of computation of a mobile system to nearby cloud servers with more computational resources through wired or wireless networks. Code offloading is considered as one of the best approaches overcoming the limited resources of mobile systems. In this paper, we analyze the factors and the performance of code offloading, especially focusing on static program partitioning and data protection. We survey state-of-the-art researches on analyzed topics. We also describe directions for future research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2323-2329
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• 2008

Advances in wireless communication and hardware technology have made it possible to manufacture high-performance tiny sensor nodes. More recently, the availability of inexpensive cameras modules that are able to capture multimedia data from the environment has fostered the development of Wireless Multimedia Sensor Networks(WMSNs). WMSN supplements the a advanced technique that senses, transmits, and processes the multimedia contents upon the text based traditional wireless sensor network. Since the amount of data which the multimedia contents have, is significantly larger than that of text based data, multimedia contents require lots of computing power and high network bandwidth. To process the multimedia contents on the wireless sensor node which has very limited computing power and energy, a technique for WMSN should take account of computing resource and efficient transmission. In the paper, we propose a new image compression technique YWCE for efficient compression and transmission of image data in WMSN. YWCE introduces 4 type of technique for motion estimation and compensation based on the Resolution Scalability of Wavelet. Experimental result shows that YWCE has high compression performance with different set of 4 type.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.9-22
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• 2022

Virtual Reality(VR) technology is an interface technology that is actively used in various audio-visual-based applications by showing users a virtual world composed of computer graphics. Since VR-based applications are graphic processing-based applications, expensive computing devices equipped with Graphics Processing Unit(GPU) are essential for graphic processing. This incurs a cost burden on VR application users for maintaining and managing computing devices, and as one of the solutions to this, a method of operating services in cloud environments is being used. This paper proposes a performance management technique to address the problem of performance interference between containers owing to GPU resource competition in container-based high-performance cloud environments in which multiple containers share a single GPU. The proposed technique reduces performance deviation due to performance interference, helping provide uniform performance-based remote VR services for users. In addition, this paper verifies the efficiency of the proposed technique through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.452-465
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• 2008

This paper proposes a light-weight, seamless integrated access control for global e-Science resource sharing. E-Science, based on Grid Computing, was designed to help scientists to remotely control and process the Grid resources such as high-end equipments and remote machines. As many researchers engage in the e-Science Grids, the researchers in a grid often have to wait for or give up use of the Grid resources, even when there are idle resources in other Grids. In this case, provided that proper compensation is given, Grid resource sharing is helpful both for the researchers and the Grids which provide their resources. But, sharing Grid resources globally is not simple, as each e-Science Grid is especially designed for resource sharing in its Virtual Organization(VO) and already has its unique access control policy for its resources. This paper proposes a new integrated access control for e-Science Grid resource sharing. The access control is light-weight without any priori service level agreement(SLA)s among the Grids which share their resources and seamless because the users can use the resources shared as the ones belonging to their Grids without their additional registration to the other Grids.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.141-154
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• 2018

As the sharing economic market grows, the subject of sharing is expanding to intangible resources such as time, experience, and expertise. The phenomenon that an individual temporarily participates in the platform by utilizing own intangible resources is defined as a 'gig economy'. The gig economy has a positive expectation that can create new jobs, but also has negative warnings that it is only a temporary job based on low wages. The gig economy market is growing rapidly in Korea, however there are very few academic discussions. This study examines the experiences of resource providers in the Korean gig economic platform, and then explores future job changes based on the perception of resource providers. This study selected the subject of research as a talent sharing platform and conducted in-depth interviews with 16 resource providers. The results of the research were presented through content analysis, and their experiences and perceptions were classified into six themes. This study implies academic and practical significance in exploring in depth the overall experience of resource suppliers and in suggesting proposals for desirable successful market growth.