• International journal of advanced smart convergence
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• v.1 no.2
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• pp.12-15
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• 2012

Energy costs for operating and cooling computing resources in Cloud infrastructure have increased significantly up to the point where they would surpass the hardware purchasing costs. Thus, reducing the energy consumption can save a significant amount of management cost. One of major approach is removing hardware over-provisioning. In this paper, we propose a technique that facilitates power saving through reducing resource over provisioning based on virtualization technology. To this end, we use dynamic workload shaping to reschedule and redistribute job requests considering overall power consumption. In this paper, we present our approach to shape workloads dynamically and distribute them on virtual machines and physical machines through virtualization technology. We generated synthetic workload data and evaluated it in simulating and real implementation. Our simulated results demonstrate our approach outperforms to when not using no workload shaping methodology.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.119-130
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• 2023

Worldwide organizations use the benefits offered by Cloud Computing (CC) to store data, software and programs. While running hugely complicated and sophisticated software on cloud requires more energy that causes global warming and affects environment. Most of the time energy consumption is wasted and it is required to explore opportunities to reduce emission of carbon in CC environment to save energy. Many improvements can be done in regard to energy efficiency from the software perspective by considering and paying attention on the energy consumption aspects of software's that run on cloud infrastructure. The aim of the current research is to propose a framework with an additional phase called parameterized development phase to be incorporated along with the traditional Software Development Life cycle (SDLC) where the developers need to consider the suggested techniques during software implementation to utilize low energy for running software on the cloud and contribute in green computing. Experiments have been carried out and the results prove that the suggested techniques and methods has enabled in achieving energy consumption.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.2
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• pp.249-253
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• 2013

This study analyzed that technological competition, variety and simility of Green IT fields using patents data. To achieve this, we limited range of Green IT that reduction of energy, eco-friendly technology. Therefore we conducted analysis of patents that power saving systems, light control system, smart system, cloud computing and green house/eco systems. As the result of that, power saving field was the most developed. The simililarty of power saving and cloud computing systems are very high and similiarities of light control system, green house/eco systems and smart system were very high.

• Kyungpook Mathematical Journal
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• v.59 no.1
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• pp.13-22
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• 2019

This paper presents a symbolic method for solving a boundary value problem with inhomogeneous Stieltjes boundary conditions over integro-differential algebras. The proposed symbolic method includes computing the Green's operator as well as the Green's function of the given problem. Examples are presented to illustrate the proposed symbolic method.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.10-17
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• 2015

Emotional computer that you want to study in a regular number change is the continuing sensitivity. Emotional Computing manner the sensibilities numbered and emotions were running through the trees. Emotional assessment of emotional sensibility computing was used as the coordinates of the key effects of the James A. Russell (Core Affect). Emotional tree runs purpose was to verify the correlation of sensitivity and emotion computing tree. Emotional tree attributes experiment color, brightness, saturation was configured with. When 50% brightness increase, about pleasure (X-axis) has increased by 10.49 points. Brightness 50%, GREEN 50% increase in the degree of pleasure (X-axis) of 10.49 points, tone (Y axis) has increased by 15.85 points. Brightness 50%, GREEN 50% increase in the degree of pleasure (X-axis) of 10.49 points, tone (Y axis) has increased by 15.85 points. Brightness 50% of the free-extent (X-axis), BLUE 50% when the tone (Y axis), pleasure extent (X-axis) of 10.49 points, tone (Y axis) as much as 14.65 points sensibilities have changed. When representatives emotions size changes have increased 50% brightness, color RED 50%, increased 5.4% Emotional excitement, emotion depressed declined -4.2%. 50% brightness, color GREEN 50% increase in emotional excitement had increased to 8.6%, declined by -5.5% this melancholy sensibility. Representative emotion and emotional changes increase or decrease the size of the emotional attributes were analyzed by quantitative methods. After the happy emotions number is needed to study more similar to the human emotion through the execution of the video image emotion emotional tree computing.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.1-5
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• 2020

Sustainable computing is a rapidly expanding field of research covering the fields of multidisciplinary engineering. With the rapid adoption of Internet of Things (IoT) devices, issues such as security, privacy, efficiency, and green computing infrastructure are increasing day by day. To achieve a sustainable computing ecosystem for future smart cities, it is important to take into account their entire life cycle from design and manufacturing to recycling and disposal as well as their wider impact on humans and the places around them. The energy efficiency aspects of the computing system range from electronic circuits to applications for systems covering small IoT devices up to large data centers. This editorial focuses on the security, privacy, and efficiency of sustainable computing for future smart cities. This issue accepted 17 articles after a rigorous review process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Advanced Industrial SCIence
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• v.2 no.4
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• pp.17-27
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• 2023

The purpose of this study is to improve the efficiency of digital conversion by presenting factors that domestic small and medium-sized manufacturers should consider when attempting digital conversion. Using SME data from 2019 to 2021, we analyze the impact of digital transformation on the financialization of enterprises and which digital technologies affect financialization, and further analyze the mediating effect of green technology innovation between digital transformation and business finance. did The results of the study support the negative impact of digital technologies on corporate finance, and cloud computing technologies have been found to significantly inhibit the level of corporate finance. In addition, it was found that green technology innovation plays a mediating role in suppressing corporate financialization by promoting green technology innovation through digital transformation. Digital transformation influences corporate decision-making through green technology innovation, suggesting that the combination of digital technology and green projects should be considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3322-3337
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• 2018

Sleep mode detection is a significant power management and green computing feature. However, it is difficult for televisions and smart TVs to detect deactivation events because we can use these devices without the assistance of an input device. In this paper, we propose a robust method for smart TVs to detect deactivation events based on a visual combination of face and motion detection. The results of experiments conducted indicate that the proposed method significantly reduces incorrect face detection and human absence by means of motion detection. The results also show that the proposed method is robust and effective for smart TVs to reduce power consumption.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.130-132
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• 2011

본 논문은 홈 네트워크 상에서 디바이스들에 대한 자동 IP 구성 관리 기술에 관한 것으로, 홈 네트워크 내의 다양한 디바이스들이 새로 설치 되거나 교체 되었을 때, 홈 네트워크 시스템의 특성에 맞게 시스템을 자동적으로 구성하고 이를 관리하기 위한 것이다. 디바이스는 IP 관리서버와 통신하여 구성 관리 정보를 교환하고, 제공된 구성 관리 정보를 통해 디바이스 구성 관리를 수행한다. 본 논문에서는 홈 네트워크 상에 새로운 디바이스가 설치되거나 교체 되었을 때 자동으로 홈 네트워크에 연결될 수 있도록 편의성을 제공하며, 잘못된 IP 설정으로 인한 문제를 해결하는 방법을 제시한다.