• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.7-14
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• 2016

Recently, as cloud computing technologies are developed, it enable to work anytime and anywhere by smart phone and computer. Also, cloud computing technologies are suited to reduce costs of maintaining IT infrastructure and initial investment, so cloud computing has been developed. As demand about cloud computing has risen sharply, problems of power consumption are occurred to maintain the environment of data center. To solve the problem, first of all, power consumption has been measured. Although using power meter to measure power consumption obtain accurate power consumption, extra cost is incurred. Thus, we propose prediction method about power consumption without power meter. To proving accuracy about proposed method, we perform CPU and Hard disk test on cloud computing environment. During the tests, we obtain both predictive value by proposed method and actual value by power meter, and we calculate error rate. As a result, error rate of predictive value and actual value shows about 4.22% in CPU test and about 8.51% in Hard disk test.

• Journal of Convergence Society for SMB
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• v.2 no.1
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• pp.19-24
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• 2012

In this paper, we propose the battery life time extension method in the multi-interface terminal by using the state information in an optical wireless integrated network architecture. When the bottlenecks occurs in the network, the terminal receives data packets via multipath. However, the battery life time is rapidly reduced because the power consumption of the terminal is bigger than single interface. For reducing the power consumption in the multi-interface terminal, the Optical Line Terminal (OLT) confirms whether the bottleneck phenomenon is occurred or not. And the network state information is transmitted to the terminal. The terminal turns one of the interfaces off to reduce the power consumption. In order to estimate the performance, we compare the power consumption between single and dual interfaces.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.162-175
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• 2018

Currently, electricity consumption and feedback mechanisms are being widely researched in Internet of Things (IoT) areas to realise power consumption monitoring and management through the remote control of appliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief network for electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring and control module is developed for automatically operating air conditioners with a gateway, which connects and controls the appliances through an embedded ZigBee solution. To collect electricity consumption data, a programmable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisation via the Internet and report the operational parameters and working states. The cloud platform manages the behaviour planning functions of the energy-saving strategies based on the power consumption features analysed by a deep belief network algorithm, which enables the automatic classification of the electricity utilisation situation. Besides increasing the user's comfort and improving the user's experience, the established feature models provide reliable information and effective control suggestions for power reduction by refining the air conditioner operation habits of each house. In addition, several data visualisation technologies are utilised to present the power consumption datasets intuitively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.509-517
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• 2015

Side Channel Analysis of applying the power-consumption was known as effective method to analyze the key of security device based on chip. The precedential information of power-consumption was measured by the voltage distribution method using by series connection of resistor. This method was dependent on the strength of the voltage. If the voltage cannot be acquired much information which is involved with the key, the information of power-consumption significantly might be influenced by noise. If so, some of the information of power-consumption might be lost and distorted. Then, this loss can reduce the performance of the analysis. For the first time, this paper will be introduced the better way of the improvement with using the method of Current to Voltage Converter with OP-Amp. The suggested method can reduce the effect of the noise which is included in the side channel information. Therefore we can verify the result of our experiments which is provided with the improvement of the performance of side channel analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.462-466
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• 2010

A new buffer cache management scheme that aims at reducing power consumption in mixed HDD and NAND flash memory storage systems is presented. The proposed scheme reduces power consumption by considering different energy-consumption rate of storage devices, I/O operation type (read or write), and reference potential of cached blocks in terms of both recency and frequency. Simulation shows that the proposed scheme reduces power consumption by 18.0% on average and up to 58.9%.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.736-744
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• 2016

Network on chip (NoC) is an emerging technology in the field of multi core interconnection architecture. The routers plays an essential components of Network on chip and responsible for packet delivery by selecting shortest path between source and destination. State-of-the-art NoC designs used routing table to find the shortest path and supports four ports for packet transfer, which consume high power consumption and degrades the system performance. In this paper, the multi port multi core router architecture is proposed to reduce the power consumption and increasing the throughput of the system. The shared buffer is employed between the multi ports of the router architecture. The performance of the proposed router is analyzed in terms of power and current consumption with conventional methods. The proposed system uses Modelsim software for simulation purposes and Xilinx Project Navigator for synthesis purposes. The proposed architecture consumes 31 mW on CPLD XC2C64A processor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1571-1574
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• 2014

In this paper, we propose a unidirectional transmission of critical information obtained by keyboard hacking or kernel and keyboard driver hacking even though the computer is not connected to the external network. We show the hacking can be attempted in the proposed method to show the way preventing such attempts in advance. Firewalls and other various methods are used to prevent the hacking from the external network but the hacking is also attempted in various ways to detour the firewall. One of the most effective way preventing from the hacking attack is physically disconnect the internal intranet systems from the external internet and most of the government systems, military systems and big corporate systems are using this way as on one of the protection method. In this paper, we show the feasibility of transmission of security codes, etc via the short message to the external network on the assumption that a hacking program such as Trojan Horse is installed on the computer systems separated from the external network. Previous studies showed that the letters on the monitor can be hijacked by electromagnetic analysis on the computer to obtain the information even though the system is not connected ti the network. Other studies showed that the security code hint can obtained by analyzing the power consumption distribution of CPU. In this paper, the power consumption distribution of externally accessible power line is analyzed to obtain the information and the information can be transmitted to the external network. Software controlling the CPU and GPU usage is designed to control the power supply of computer. The sensors such as the Rogowski coils can be used on the external power line to collect the data of power consumption change rates. To transmit the user password by short message, due to the capacitive components and the obstacle from other power supply, A very slow protocol are used.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• The KIPS Transactions:PartA
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• v.18A no.3
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• pp.93-98
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• 2011

While the use of battery-powered embedded systems has been rapidly increasing, the current level of battery technology has not kept up with the drastic increase in power consumption by the system. In order to prolong system usage time, the battery size needs to be increased. The amounts of power consumption by embedded systems are determined by their hardware configuration and software for manipulating hardware resources. In spite of that, the hardware provides features for lowering power consumption, if those cannot be utilized efficiently by software including operating system, reduction in power consumption is not optimized. In this paper, we propose a BET(Break Even Time)-based scheduling method using task partition to reduce power consumption of multimedia applications in a mobile embedded system environment.