• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.75-80
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• 2009

In this study, a Web server was constructed using LabVIEW's DataSocket, which makes possible acquisition, analysis, and saving in real time. The output value of the optical current sensor at the web server PC was measured and the output value was displayed using the Web browser of the client PC. DataSocket by LabVIEW makes the construction of a Web server easier than other languages and is compatible with other application programs. An optical current sensor was composed using a 1310 [nm] laser diode, and 9/125 [${\mu}m$] standard single mode optical fiber and was created to be a close type sensor. Data measurement using Web servers has the advantage of monitoring electric power systems at a great distance and can fuse IT technology and electric power systems. Also, this measurement uses inexpensive mounting and programming when compared to existing measurement equipment allowing the construction of a measurement system in any situation or surrounding.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.1033-1048
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• 2018

This paper proposes an integrated lighting enabler system (ILES) based on standard machine-to-machine (M2M) platforms. This system provides common services of end-to-and M2M communication for smart lighting system. It is divided into two sub-systems, namely end-device system and server system. On the server side, the M2M platform OpenMTC is used to receive data from the sensors and send response for activating actuators. At the end-device system, a programmable smart lighting device is connected to the actuators and sensors for communicating their data to the server. Some experiments have been done to prove the system concept. The experiment results show that the proposed integrated lighting enabler system is effective to reduce the power consumption by 25.22% (in average). The proving of significance effect in reducing power consumption is measured by the Wilcoxon method.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.22-29
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• 2022

Recently, with the development of mobile computing power, mobile-based VR and AR services are being developed. Due to network performance and computing power constraints, VR and AR services using large-capacity 3D content have limitations. A study on an efficient 3D content load method for a mobile device is required. The conventional method downloads all 3D content used for AR services at the same time. In this paper, we propose an active 3D content load according to the user's track. The proposed method is a partitioned 3D object load. Edge servers were installed for each area and connected through the MESH network. Partitioned load the required 3D object in the area referring to the user's location. The location is identified through the edge server information of the connected AP. The performance of the proposed method and the conventional method was compared. As a result of the comparison, the proposed method showed a stable Mobile AR Service. The results of this study, it is expected to contribute to the activation of edge server-based AR mobile services.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.403-411
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• 2014

In this paper, an algorithm of extracting the features of home appliances and automatically building a database to identify home appliances is designed and presented. For the verification, a software library supporting this algorithm is implemented and added to an power management system server, which was already implemented to support real-time monitoring of home appliances' power consumption status and controlling their power. The implemented system consists of a system server and clients, each of which measures the power consumed by a home appliance plugged in it and transmits the information to the server in real-time over a wireless network. Through experiments, it is verified that it is possible to identify any home appliance connected to a specific client.

• Journal of Power Electronics
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• v.15 no.3
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• pp.634-643
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• 2015

This paper presents a high frequency design approach for improving efficiency over a wide load range in the self-driven phase-shifted full-bridge converters for server power systems. In the proposed approach, a detailed ZVS analysis of the lagging leg switches in both the continuous conduction mode (CCM) and the discontinuous conduction mode (DCM) is presented. The optimum dead time and the determination of the appropriate operation mode are given for high efficiency according to the load conditions. Finally, the optimum operation conditions are defined to achieve a high-efficiency. A laboratory prototype operating at 80 kHz, rated 1 kW (12 V-83.3 A), is built to verify proposed theoretical analysis and evaluations. The experimental results show that the maximum efficiency is achieved as 95% and 83.5% at full load and 5% load conditions, respectively.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.227-228
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• 2008

This paper presents monitoring system based on IEC61400-25 for 750kW-class DFIG wind power generation system. It is consists of wind turbine PLC, Local and Remote I/O Server, human machine interface, and Web-server. Proposed System has been demonstrated in Daegi-ri, Kangwon-do, which aims to test IEC61400-25 communication capability of monitoring system and evaluate the performance of 750kW-class WTS.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.1-7
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• 2016

An uninterruptible power supply (UPS) allows small companies and domestic users to cope with power outages; but existing designs lack flexibility of control and require expensive battery maintenance, with a cost proportional to the outage compensation time. We combine a compact synchronous generator with a battery, with 10% of the capacity that would otherwise be required, to obtain a UPS with reduced maintenance costs for the same performance. Any UPS must respond immediately to a power loss, and our uninterruptible generator supply (UGS) is therefore built around real-time scheduling of its internal operations; this also makes it suitable for integration into the industrial gateway. The UGS is based on a real-time operating system, with an integrated wireless module providing connectivity to a web server, for monitoring and management, which can be performed remotely on a mobile device.

• Journal of Power Electronics
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• v.16 no.1
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• pp.121-132
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• 2016

In this paper, high-efficiency design methodology of a zero-voltage-switching full-bridge (ZVS-FB) pulse width modulation (PWM) converter for server-computer power supply is discussed based on self-driven synchronous rectifier (SR) performance. The design approach focuses on rectifier conduction loss on the secondary side because of high output current application. Various-number parallel-connected SRs are evaluated to reduce high conduction loss. For this approach, the reliability of gate control signals produced from a self-driver is analyzed in detail to determine whether the converter achieves high efficiency. A laboratory prototype that operates at 80 kHz and rated 1 kW/12 V is built for various-number parallel combination of SRs to verify the proposed theoretical analysis and evaluations. Measurement results show that the best efficiency of the converter is 95.16%.