• Journal of KIISE:Computer Systems and Theory
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• v.35 no.6
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• pp.273-283
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• 2008

Many embedded real-time systems have adopted processors supported with dynamic voltage scaling(DVS) recently. Power is one of the important metrics for optimization in the design and operation of embedded real-time systems. We can save considerable energy by using slowdown of processor supported with DVS. In this paper, we propose heuristic algorithms to calculate task slowdown factors for an efficient energy consumption in embedded real-time systems with task synchronization. The previous algorithm has a following constraint : given the tasks are ordered in a nondecreasing order of their relative deadline, the task slowdown factors computed are in a nonincreasing order. In this paper, we relax the constraint and propose heuristic algorithms which have the same time complexity that previous algorithm has and can save more energy. Experimental results show that the proposed algorithms are energy efficient.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.133-140
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• 2007

Since early times, captain have been sailing to select the optimum route considering the weather, ship loading status condition and operational scheduling empirically. However, it is rare to find digitalized onboard route support system whereas weather facsimile or wave and swell chart are utilized for the officer, based on captain's experience. In this paper, optimal route safety assessment system which is composed of voyage efficiency and safety component is introduced. Optimum route minimizea ETA(estimated time of arrival) and fuel consumption that shipping company and captain are requiring to evaluate for efficient voyage considering speed loss and power increase based on wave added resistance of ship. In the view point of safety, seakeeping prediction is performed based on 3 dimensional panel method. Finally, It is assistance measure for ship's optimum navigation route safety planning & assessment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.18-26
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• 2009

When channel state information (CSI) is available at the transmitter, the system throughput can be enhanced by adaptive transmissions and opportunistic multiuser scheduling. In this paper, we consider multiple-input multiple-output (MIMO) systems employing bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM). We first propose a bit-loading algorithm based on the Levin-Campello algorithm for the BIC-OFDM. Then we will apply this algorithm to the MIMO system with a finite set of constellations, by reassigning residual power on each stream Simulation results show that proposed bit-loading scheme which takes the residual power into account improves the system performance especially at high signal-to-noise ratio (SNR) range.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.109-119
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• 2013

This paper presents the design of the Safety Programmable Logic Controller (SPLC) used in the Nuclear Power Plants, an analysis of a reliability for the SPLC using a markov model. The architecture of the SPLC is designed to have the multiple modular redundancy composed of the Dual Modular Redundancy(DMR) and the Triple Modular Redundancy(TMR). The operating system of the SPLC is designed to have the non-preemptive state based scheduler and the supervisory task managing the sequential scheduling, timing of tasks, diagnostic and security. The data communication of the SPLC is designed to have the deterministic state based protocol, and is designed to satisfy the effective transmission capacity of 20Mbps. Using Markov model, the reliability of SPLC is analyzed, and assessed. To have the reasonable reliability such as the mean time to failure (MTTF) more than 10,000 hours, the failure rate of each SPLC module should be less than $2{\times}10^{-5}$/hour. When the fault coverage factor (FCF) is increased by 0.1, the MTTF is improved by about 4 months, thus to enhance the MTTF effectively, it is needed that the diagnostic ability of each SPLC module should be strengthened. Also as the result of comparison the SPLC and the existing safety grade PLCs, the reliability and MTTF of SPLC is up to 1.6-times and up to 22,000 hours better than the existing PLCs.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.49-68
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• 2008

The purpose of this paper is to extensively review the condition monitoring (CM) techniques using empirical models in an effort to reduce or eliminate unexpected downtimes in general industry, and to illustrate the feasibility of applying them to the nuclear industry. CM provides on-time warnings of system states to enable the optimal scheduling of maintenance and, ultimately, plant uptime is maximized. Currently, most maintenance processes tend to be either reactive, or part of scheduled, or preventive maintenance. Such maintenance is being increasingly reported as a poor practice for two reasons: first, the component does not necessarily require maintenance, thus the maintenance cost is wasted, and secondly, failure catalysts are introduced into properly working components, which is worse. This paper first summarizes the technical aspects of CM including state estimation and state monitoring. The mathematical background of CM is mature enough even for commercial use in the nuclear industry. Considering the current computational capabilities of CM, its application is not limited by technical difficulties, but by a lack of desire on the part of industry to implement it. For practical applications in the nuclear industry, it may be more important to clarify and quantify the negative impact of unexpected outcomes or failures in CM than it is to investigate its advantages. In other words, while issues regarding accuracy have been targeted to date, the concerns regarding robustness should now be concentrated on. Standardizing the anticipated failures and the possibly harsh operating conditions, and then evaluating the impact of the proposed CM under those conditions may be necessary. In order to make the CM techniques practical for the nuclear industry in the future, it is recommended that a prototype CM system be applied to a secondary system in which most of the components are non-safety grade. Recently, many activities to enhance the safety and efficiency of the secondary system have been encouraged. With the application of CM to nuclear power plants, it is expected to increase profit while addressing safety and economic issues.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.509-520
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• 2007

In this paper, we propose a real-time sensor node platform that guarantees the real-time scheduling of periodic and aperiodic tasks through a multitask-based software decomposition technique. Since existing sensor networking operation systems available in literature are not capable of supporting the real-time scheduling of periodic and aperiodic tasks, the preemption of aperiodic task with high priority can block periodic tasks, and so periodic tasks are likely to miss their deadlines. This paper presents a comprehensive evaluation of how to structure periodic or aperiodic task decomposition in real-time sensor-networking platforms as regard to guaranteeing the deadlines of all the periodic tasks and aiming to providing aperiodic tasks with average good response time. A case study based on real system experiments is conducted to illustrate the application and efficiency of the multitask-based dynamic component execution environment in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. It shows that our periodic and aperiodic task decomposition technique yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.988-996
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• 2012

Assuming perfect channel state information (CSI), the conventional interference alignment (IA) algorithm in the uplink cellular system suppresses inter-cell interference (ICI) by aligning ICI to a randomly selected reference vector. However, IA in practice relies on limited feedback between base stations and users, resulting in residual ICI. In this paper, we propose the optimization of the reference vector that minimizes the upper-bound of residual ICI power. Secondly, the iterative IA that designs the direction of transmit and receive filter is proposed to minimize the residual ICI as well as maximize the desired signals. Moreover, we propose the user scheduling method combined with proposed IA schemes which provides the multiuser diversity gain in multi-cell environments. Finally, the performance gain of the proposed IA algorithms compared with the existing IA are analyzed and demonstrated by simulation results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1495-1504
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• 2013

Renewable energy integration and increased system complexities make system operator maintain supply and demand balance harder than before. To keep the grid frequency in a stable range, an appropriate spinning reserve margin should be procured with consideration of ever-changing system situation, such as demand, wind power output and generator failure. This paper propose a novel concept of dynamic reserve, which arrange different spinning reserve margin depending on time. To investigate the effectiveness of the proposed dynamic reserve, we developed a new short-term reliability criterion that estimates the probability of a spinning reserve shortage events, thus indicating grid frequency stability. Uncertainties of demand forecast error, wind generation forecast error and generator failure have been modeled in probabilistic terms, and the proposed spinning reserve has been applied to generation scheduling. This approach has been tested on the modified IEEE 118-bus system with a wind farm. The results show that the required spinning reserve margin changes depending on the system situation of demand, wind generation and generator failure. Moreover the proposed approach could be utilized even in case of system configuration change, such as wind generation extension.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.1-15
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• 2001

Recently, Internet based Electronic Commerce is recognized as one of the alternatives for strengthening sales power of small and medium companies. However, small and medium manufacturers can't adjust properly to the new environment because they are in short of money, personnel, and technology. To cope with this problem, this paper deals with the development of virtual manufacturing agent to support sales agent. The sales activity of most of parts manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the parts manufacturing is closely coupled with the load status of the production lines. On deciding whether to accept an order or not, as well as negotiating with buyers, sales person needs information such as load and schedule of production lines, manufacturability of the order. Therefore, the functions of virtual manufacturing agents manufacturability analysis, process planning, and scheduling are key features in developing an agent of sales activity for the parts manufacturing business. While most of research on virtual manufacturing system so far is focused on the simulation of each product, this paper deals with the development of agent assisting internet-based product sales by supporting production information promptly. The pilot system of virtual manufacturing agent is implemented using KQML-based agent template and Java-based expert system shell for a small molding company.