• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.1-10
• /
• 2021

In recent decades, the heterogeneous and dynamic behavior of Internet traffic has placed new demands on the adaptive resource allocation of the optical network infrastructure. However, the advent of multifiber elastic optical networks has led to a higher degree of spectrum fragmentation than conventional flexible grid networks due to the dynamic and random establishment and removal of optical connections. In this paper, we propose heuristic routing and dynamic slot allocation algorithms to minimize spectrum fragmentation and reduce the probability of blocking future connection requests by considering the power consumption in elastic multifiber elastic optical networks.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.5
• /
• pp.59-69
• /
• 2011

Since power analysis attack which uses a characteristic that power consumed by crypto device depends on processed data has been proposed, many logics that can block these correlation originally have been developed. DRP logic has been adopted by most of logics maintains power consumption balanced and reduces correlation between processed data and power consumption. However, semi-custom design is necessary because recently design circuits become more complex than before. This design method causes unbalanced design pattern that makes DRP logic consumes unbalanced power consumption which is vulnerable to power analysis attack. In this paper, we have developed new logic style which adds another discharge phase to discharge two output nodes at the same time based on DyCML to remove this unbalanced power consumption. Also, we simulated 1bit fulladder to compare proposed logic with other logics to prove improved performance. As a result, proposed logic is improved NED and NSD to 60% and power consumption reduces about 55% than any other logics.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.4A
• /
• pp.393-401
• /
• 2006

Energy consumption is an important design parameter for battery-operated embedded systems. Dynamic power management is one of the most well-known low-power design techniques. This paper proposes an online realtime scheduling algorithm, which we call energy-aware realtime scheduling using slack stealing (EARSS). The proposed algorithm gives the highest priority to the task with the largest degree of device overlap when the slack time exists. Scheduling result enables an efficient power management by reducing the number of state transitions. Experimental results show that the proposed algorithm can save the energy by 23% on average compared to the DPM-enabled system scheduled by the EDF algorithm.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.9 no.3
• /
• pp.100-107
• /
• 2001

The main goals of the automotive suspension systems are to isolate roadway unevenness from the tire and to improve vehicle stability. To overcome the performance limitation of the passive systems the active systems which completely replace the passive spring and damper elements with a force generating actuator has been studied. However, application of the system has been limited because it has required a significant amount of power. Recently, alternative systems which retain passive elements but include active elements have been developed to reduce the power required. Those systems are mostly focused on the control system which compresses the spring-damper directly. In this study, a new type of power efficient control system which makes the spring-damper unit slide in side way is studied. After constructing the control system including dynamic modeling and motion control, two types of alternative control systems are compared in view of power consumption and dynamic attitudes such as roll responses as well as heave responses. Also, a half car bond graph model is developed to show clearly the significant differences in performances between two control systems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.30 no.3
• /
• pp.130-142
• /
• 2018

We use heat pumps with thermal storage system to reduce peak usage of electric power during winters and summers. A heat pump stores thermal energy in a thermal storage tank during the night, to meet load requirements during the day. This system stabilizes the supply and demand of electric power; moreover by utilizing the inexpensive midnight electric power, thus making it cost effective. In this study, we propose a system wherein the thermal storage tank and heat pump are modeled using the TRNSYS, whereas the control simulations are performed by (i) conventional control methods (i.e., thermal storage priority method and heat pump priority method); (ii) region control method, which operates at the optimal part load ratio of the heat pump; (iii) load response control method, which minimizes operating cost responding to load; and (iv) dynamic programming method, which runs the system by following the minimum cost path. We observed that the electricity cost using the region control method, load response control approach, and dynamic programing method was lower compared to using conventional control techniques. According to the annual simulation results, the electricity cost utilizing the load response control method is 43% and 4.4% lower than those obtained by the conventional techniques. We can note that the result related to the power cost was similar to that obtained by the dynamic programming method based on the load prediction. We can, therefore, conclude that the load response control method turned out to be more advantageous when compared to the conventional techniques regarding power consumption and electricity costs.

• The Journal of the Korea Contents Association
• /
• v.6 no.12
• /
• pp.71-79
• /
• 2006

Recently, embedded systems like mobile and portable devices are quickly disseminated around the world. Since these.devices need more computation power as the applications become gradually complicated, the bettery lifetime becomes the most serious constraints. So research efforts have been focused on reducing the power consumption, resulting in producing devices with low-power H/W and S/W components. In this paper, we propose a low-power Java API set using the dynamic power management (DPM) scheme in the J2ME Java Platform on the real-time operating system UbiFOSTM and show that we could save energy up to 30% through experiments using the API set.

• ETRI Journal
• /
• v.33 no.3
• /
• pp.407-414
• /
• 2011

In an effort to reduce energy consumption, research into adaptive power management in real-time systems has become widespread. In this paper, a novel dynamic voltage scaling scheme is proposed for multiprocessor systems. Based on the concept of the Nash bargaining solution, a processor's clock speed and supply voltage are dynamically adjusted to satisfy these conflicting performance metrics. In addition, the proposed algorithm is implemented to react adaptively to the current system conditions by using an adaptive online approach. Simulation results clearly indicate that the superior performance of the proposed scheme can strike the appropriate performance balance between contradictory requirements.

• Journal of Information Processing Systems
• /
• v.20 no.2
• /
• pp.226-238
• /
• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• Proceedings of the IEEK Conference
• /
• 2003.07b
• /
• pp.967-970
• /
• 2003

A new adder-and-accumulator (A$^2$C) adapted to pipelined Δ$\Sigma$ modulators is proposed in this paper. With the viewpoint of area consumption, registers are removed in the existing pipelined Δ$\Sigma$ modulator, and then adder and accumulator are merged. In order to optimize area consumption, speed and power consumption, dynamic carry look-ahead adder (CLA) is adopted in $A^2$C. Moreover, a guideline for the transistor sizing in CLA with regard to the minimization of the energy-delay-area product (EDAP) is proposed[1]. The proposed $A^2$C has been verified by HSPICE simulations.

• Transactions of the Korean hydrogen and new energy society
• /
• v.34 no.6
• /
• pp.773-784
• /
• 2023

In this study, a comparative analysis between an electric heat pump cooling system and a hybrid desiccant cooling system is conducted. Desiccant cooling is a thermal driven system with potentially lower electric power consumption than electric heat pump. Hybrid desiccant cooling system simulation includes components such as a desiccant rotor, direct and indirect evaporative coolers, heat exchangers, fans, and a heat pump system. Using dynamic simulations by climate conditions, house cooling temperatures and power consumption for both systems are analyzed for 16 days period in the summer season under climate scenarios for the year 2100 prediction. The results reveal that the hybrid desiccant cooling system exhibits a 5-18% reduction in electric consumption compared to the heat pump system.