• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2631-2649
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• 2021

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leadsto reliable connectivity with minimal power consumption in wireless communication. The power control in D2D is modeled as a non-cooperative game. Each device is allowed to independently select and transmit its power to maximize (or minimize) user utility. The aim is to guide user devices to converge with the Nash equilibrium by establishing connectivity with network resources. The proposed algorithm with pricing factors is used for power consumption and reduces overall interference of D2Ds communication. The proposed algorithm is evaluated in terms of the energy efficiency of the average power consumption, the number of D2D communication, and the number of iterations. Besides, the algorithm has a relatively fast convergence with the Nash Equilibrium rate. It guarantees that the user devices can achieve their required Quality of Service (QoS) by adjusting the residual cost coefficient and residual energy factor. Simulation results show that the power control shows a significant reduction in power consumption that has been achieved by approximately 20% compared with algorithms in [11].

• 인터넷정보학회논문지
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• 제17권1호
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• pp.7-14
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• 2016

최근 클라우드 컴퓨팅 기술이 발전함에 따라, 언제 어디서나 스마트 폰이나 컴퓨터로 접속하여 업무를 처리할 수 있다. 또한 IT 인프라를 구축하기 위한 초기투자비용과 유지보수에 대한 부담을 줄이는 방안으로 적합하다고 여겨지면서 클라우드 컴퓨팅은 발전하였다. 클라우드 컴퓨팅의 수요가 급격하게 늘어남에 따라, 데이터센터의 환경을 유지하기 위해 소비되는 전력에 관한 문제가 발생하였다. 이 문제를 해결하기 위해서는 먼저 소비전력을 측정할 수 있어야 한다. 비록 전력측정기를 이용하여 소비전력을 측정하는 것은 정확한 소비전력을 얻을 수 있지만, 추가비용이 발생한다. 따라서 본 논문에서는 전력측정기에 의존하지 않고 소비전력을 예측하는 방안을 제시한다. 제시한 방안의 정확성을 입증하기 위해 클라우드 컴퓨팅 환경에서 CPU와 Hard disk 테스트를 실시하였다. 테스트가 진행되는 동안, 제안한 방안과 전력측정기에 의해 예측 값과 실제 값을 얻고. 오차율을 계산하였다. 그 결과 CPU 테스트에서 예측 값과 실제 값의 차이는 약 4.22%이고, Hard disk 테스트에서는 약 8.51%을 보였다.

• 중소기업융합학회논문지
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• 제2권1호
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• pp.19-24
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• 2012

본 논문에서는 네트워크 상황 정보를 이용한 다중 인터페이스 단말의 배터리 수명 연장 방법을 제안한다. 단말은 현재 접속 네트워크에 병목현상이 발생하는 경우, 다중 인터페이스를 이용하여 다중 경로로 데이터를 수신한다. 하지만 다중 인터페이스를 이용하는 경우 단말의 배터리 소모가 많아 단말의 배터리 수명이 짧아진다. 이러한 배터리 소모를 줄이기 위해 OLT를 통해 네트워크의 병목현상 유무를 판단하고 단말에게 네트워크 상황 정보를 전송한다. 단말은 네트워크 상황 정보를 통해 하나의 인터페이스를 비활성화 시켜 에너지 소비를 절감시킨다. 단일 인터페이스와 다중 인터페이스를 사용함에 따른 배터리 소비량을 계산하여 제안 방안의 효과를 확인하였다.

• Journal of Information Processing Systems
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• 제14권1호
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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.

• 정보보호학회논문지
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• 제25권3호
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• pp.509-517
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• 2015

전력소비를 이용한 부채널 분석은 Chip 기반의 보안디바이스의 키를 해독하는 효과적인 방법으로 알려져 있다. 기존의 전력소비정보는 저항의 직렬연결을 이용한 전압분배 방식을 사용한다. 이 방법은 디바이스에 인가되는 전압의 크기에 종속적이며. 그 크기가 작은 경우 노이즈의 영향을 크게 받아 신호 왜곡이 발생되고, 일부 신호 손실이 발생된다. 이와 같은 이유는 부채널 분석의 성능을 저하 시킨다. 본 논문에서는 OP-Amp를 이용한 전류-전압 변환방식을 적용하여 전력소비 정보를 계측함으로써 부채널 분석의 성능을 향상시킬 수 있는 방법을 제시한다. OP-Amp를 이용한 전류-전압 변환방식을 사용하여 전력소비 정보에 포함되는 노이즈의 영향을 줄일 수 있다. 따라서 부채널 분석의 성능을 향상됨을 실험을 통해 검증한다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권4호
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• pp.462-466
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• 2010

본 논문은 하드디스크와 NAND 플래시메모리를 동시에 사용하는 저장 시스템 환경에서 전력 소모를 최소화하는 버퍼 캐쉬 관리 기법을 제안한다. 저장장치별 전력 소모율과 입출력 연산 종류(읽기 또는 쓰기) 및 블록의 재참조 가능성(최근성 및 빈도)을 통합적으로 고려하는 버퍼 캐쉬 관리 기법의 설계로 저장 시스템의 전력 소모량을 평균 18.0%, 최대 58.9%까지 줄일 수 있음을 보인다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권6호
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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.

• 전기학회논문지
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• 제63권11호
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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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• 제17권3호
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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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• 제30권1호
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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.