• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.671-678
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• 2022

Approximate computing is an computational technique that is acceptable degree of inaccurate results of accurate results. Approximate multiplication is one of the approximate computing methods for high-performance and low-power computing. In this paper, we propose a high-density, low-power, and high-speed approximate multiplier using approximate 4-2 compressor and improved full adder. The approximate multiplier with approximate 4-2 compressor consists of three regions of the exact, approximate and constant correction regions, and we compared them by adjusting the size of region by applying an efficient partial product reduction. The proposed approximate multiplier was designed with Verilog HDL and was analyzed for area, power and delay time using Synopsys Design Compiler (DC) on a 25nm CMOS process. As a result of the experiment, the proposed multiplier reduced area by 10.47%, power by 26.11%, and delay time by 13% compared to the conventional approximate multiplier.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.1
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• pp.1-7
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• 2006

In this paper, a novel power management structure for an energy harvesting pervasive system is proposed. The system considers the power state of each subsystem to assign proper power sources. The switch matrix structure utilizes each power source to reduce the peak current of the battery. The power management structure can be interfaced to an embedded system power supply without significant design change.

• The Journal of Information Systems
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• v.19 no.4
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• pp.87-109
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• 2010

The ubiquitous computing & technology is to make passive IT machinery as the smart-object to solve the problems of information management. These ubiquitous devices can be a concierge of humans lives. In addition, the ubiquitous computing & technology added with Pro-Active processing technology is the intellectual automatic process capacity that probably enhance quality of human's life. Although the social influencing power of ubiquitous computing technology is so critical, research on the social impact of ubiquitous has been studied insufficiently. And, we also need the countermeasures to protect the societies from the side effect of the ubiquitous computing technology. The purpose of this research is to minimize the loss which comes from the new ubiquitous society, by presenting the technological and systematic alternatives and by researching the various side effects. This research suggests the proper alternatives by reviewing and by researching the adverse effects of the ubiquitous computing technology.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.928-933
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• 2003

For simulation of three-dimensional turbulent flow with LES and DNS takes much time and expense with current available computing resources. It is nearly impossible to simulate turbulent flow with high Reynolds number. So, the emerging alternative is the Grid computing for needed computation power and working environment. In this study, the CFD code was parallelized to adapt it for the parallel computing under the Grid environment. In the first place, the Grid environment was built to connect the PC-Cluster facilities belong to the different institutions using communication network system. And CFD applications were calculated to check the performance of the parallel code developed for the Grid environment. Although it is a fundamental study, it brings about a important meaning as first step in research of the Grid.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1136-1140
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• 2022

This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.24-30
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• 2014

This study investigates computing offloading effect of cloud in real-time video personal broadcast service, whose server is mobile device. Mobile device does not have enough computing resource for encoding video. The computing burden is offloaded to cloud, which has abundant resources in terms of computing, power, and storage compared to mobile device. By reducing computing burden, computation energy can be saved while transmission data amount increases because of decreasing compression efficiency. This study shows that the optimal operation point can be found adaptively to time-varying LTE communication condition result of tradeoff analysis between offloaded computation burden and increase in amount of transmitted data.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.8-17
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• 2014

Petascale systems(so called supercomputers) have been mainly used for supporting communication-intensive and tightly-coupled parallel computations based on message passing interfaces such as MPI(HPC: High-Performance Computing). On the other hand, computing paradigms such as High-Throughput Computing(HTC) mainly target compute-intensive (relatively low I/O requirements) applications consisting of many loosely-coupled tasks(there is no communication needed between them). In Korea, recently emerging applications from various scientific fields such as pharmaceutical domain, high-energy physics, and nuclear physics require a very large amount of computing power that cannot be supported by a single type of computing resources. In this paper, we present our HTCaaS(High-Throughput Computing as a Service) which can leverage national distributed computing resources in Korea to support these challenging HTC applications and describe the details of our system architecture, job execution scenario and case studies of various scientific applications.

• Journal of Power Electronics
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• v.13 no.4
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• pp.729-736
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• 2013

Knowledge of a power semiconductor's operating temperature is important in circuit design and converter control. Designing appropriate circuitry that does not affect regular circuit operation during virtual junction temperature measurement at actual operating conditions is a demanding task for engineers. The proposed method enables virtual junction temperature estimation with a dedicated modified gate driver circuit based on real-time measurement of a semiconductor's quasi-threshold voltage. A simulation was conducted before the circuit was designed to verify the concept and to determine the basic properties and potential drawbacks of the proposed method.