• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.12
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• pp.96-104
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• 2009

In the real system environments, the performance of the application is not linearly proportional to the clock frequency of the microprocessor, in contrast to the general assumption of conventional dynamic voltage scaling. In this paper, we analytically model the relation between the performance of the application and the clock frequency of the microprocessor, and introduce the energy-optimal scheduling algorithm for a task set with distinct application characteristics. In addition, we present a theorem for the energy-optimal scheduling, which the derivative of the energy consumption with respect to the execution time should be the same for all the tasks. The proposed scheduling algorithm always generates the energy-optimal scaling factor thanks to the theorem for energy-optimal scheduling. We achieved about 7% additional energy reduction in the experiments using synthetic task sets.

• Journal of the Korea Society for Simulation
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• v.23 no.2
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• pp.65-72
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• 2014

Sensor nodes are easily compromised by attacker when which are divided in open environment. The attacker may inject false report and false vote attack through compromised sensor node. These attacks interrupt to transmission legitimate report or the energy of sensor node is exhausted. PVFS are proposed by Li and Wu for countermeasure in two attacks. The scheme use inefficiency to energy of sensor node as fixed report threshold and verification node. In this paper, our propose the next neighbor node selection scheme based on fuzzy logic system for energy improvement of PVFS. The parameter of fuzzy logic system are energy, hops, verification success count, CH select high the next neighbor node among neighbor nodes of two as deduction based on fuzzy logic system. In the experimental, our proposed scheme was improvement to energy of about 9% compare to PVFS.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.14-22
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• 2007

Wireless sensor networks are composed of numerous sensor nodes and exchange or recharging of the battery is impossible after deployment. Thus, sonsor nodes must be very energy-efficient. As neighboring sensor nodes generally have the data of similar information, duplicate transmission of similar information is usual. To prevent energy wastes by duplicate transmissions, it is advantageous to organize sensors into clusters. The performance of clustering scheme is influenced by the cluster-head election method and the size or the number of clusters. Thus, we should optimize these factors to maximize the energy efficiency of the clustering scheme. In this paper, we propose a new energy consumption model for LEACH which is a well-known clustering protocol and determine the optimal number of clusters based on our model. Our model has accuracy over 80% compared with the simulation and is considerably superior to the existing model of LEACH.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.137-143
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• 2015

During the past 30 years, DRAM has been used for the reasons of economic efficiency of the production. Recently, PRAM has been emerged to overcome the shortcomings of DRAM. In this paper, we propose a technique that can reduce energy consumption by use of a narrow values to the write operation of PRAM. For this purpose, we describe the data compression method using a narrow value and the architecture of PRAM, We also experiment under the Simplescalar 3.0e simulator and SPEC CPU2000 benchmark environments. According to the experiments, the data hit rate of PRAM was increased by 39.4% to 67.7% and energy consumption was reduced by 9.2%. In order to use the proposed technique, it requires 3.12% of space overhead per word, and some additional hardware modules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1034-1042
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• 2010

As many researchers have been interested in Green IT, Energy Efficient Ethernet(EEE) with rate adaptation has recently begun to receive many attention. However, the rate adaptation scheme can have different energy efficiency and delay according to the characteristics of various traffic patterns. Therefore, in this paper, we analyze the impact of different traffic patterns on the energy efficiency and delay in Ethernet with rate adaptation. To do this, firstly we design a rate adaptation simulator which consists of Poisson based traffic generator, Pareto distribution based ON-OFF generator and Ethernet node with rate adaptation by using OPNET Modeler. Using this simulator, we perform the simulation in view of the total number of switching, transmission rate reduction, energy saving ratio and average queueing delay. Simulation results show that IP traffic patterns with high self-similarity affect the number of switching, rate reduction and energy saving ratio. Additionally, the transition overhead is caused due to the high self-similar traffic.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.83-93
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• 2007

In this paper, we address a power-aware scheduling algorithm for a mixed real-time system which consists of periodic and sporadic tasks, each of which is characterized by its minimum period, worst-case execution requirement and deadline. We propose a dynamic voltage scaling algorithm called DVSMT(DVS for mixed tasks), which dynamically scales down the supplying voltage(and thus the frequency) using on-line distribution of the borrowed resources when jobs complete while still meeting their deadlines. With this scheme, we could reduce more energy consumption. As the proposed algorithm can be easily incorporated with RTOS(Real-Time Operating System), it is applicable for handhold devices and sensor network nodes that use a limited battery power. Simulation results show that DVSMT saves up 60% more than the existing algorithms both in the periodic-task and mixed-task systems.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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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 activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Proceedings of the KIEE Conference
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• 2006.07e
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• pp.85-86
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• 2006

최근 정부에서는 고효율 기기 개발과 ESCO 사업 등을 통해 낭비되고 있는 에너지를 절감하기 위해 노력하고 있고, 산업 패러다임 변화에 따른 전력 IT 기술 중요성이 상승하고 있어 디지털 멀티미디어 기술과 융합된 지능형 전원 관리시스템 개발이 필요한 실정이다. 따라서 본 연구에서는 리모콘 및 인체감지에 의한 스위치 및 콘센트의 개별/동시 제어기법을 이용한 지능형 전원 관리 시스템 개발하고 특성실험을 통해 우수성을 입증하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.125-135
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• 2010

Recently, the problem of global warming has issued seriously, so Green IT(Information Technology) using RFID/USN is concerned in order to solve environmental problems. In this paper, we implemented that public area like an underground parking lot could reduce unnecessary energy consumption used by lighting control system based on Ubiquitous Sensor Networks. The lighting control system for underground parking lot is comprised of intersection nodes for watching cars enter and leave, and light node for controlling light. It applies the routing protocol based on hierarchical cluster, hierarchical addressing method, and probability filtering method for the specific place like an underground parking lot. The result after experiments shows that the lighting control system could decrease electrical energy consumption to around 61.7%.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.3-8
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• 2014

We consider a limited feedback based hybrid beamforming which reduces the energy of feedback information. In the millimeter wave channel, some rays with large ray gain dominate energy of the channel. Using this point, we propose a channel feedback scheme that employs limited number of channel rays. Also, we provide a hybrid beamforming scheme for the limited feedback system. Based on the simulation results, the proposed scheme shows a comparable data rate performance with conventional schemes, while it remarkably reduces energy of channel feedback.