• Clinical and Experimental Pediatrics
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• v.63 no.4
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• pp.117-118
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• 2020

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1096-1111
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• 1999

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1449-1456
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• 2016

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.68-74
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• 2005

In deadline scheduling, jobs have deadlines by which they are completed. The scheduling algorithm determines which jobs are executed at each time. Then only the completed jobs contribute to the throughput or gain of the algorithm. The jobs have arbitrary weights and the gain of the algorithm is given as the sum of weights of the completed jobs. The goal of the scheduling algorithm is to maximize its gain. In this paper, we consider online non-preemptive scheduling, where jobs arrive online and the scheduling algorithm has no information about jobs arriving ahead. Also the jobs cannot be preempted or rejected while they are executed. For this problem, we obtain lower bounds for any online algorithms and also we propose an optimal online algorithm meeting the lower bounds.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1219-1230
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• 2003

We analyze an integrated voice/data CDMA system, where the whole channels are divided into voice prioritized channels and voice non-prioritized channels. For real-time voice service, a preemptivc priority is granted in the voice prioritized channels. And, for delay-tolerant data service, the employment of buffer is considered. On the other hand, the transmission permission probability in best-effort packet-data service is controlled by estimating the residual capacity available for users. We build a 2-dimensional markov chain about prioritized-voice and stream-data services and accomplish numerical analysis in combination with packet-data traffic based on residual capacity equation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.729-738
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• 1995

We consider a priority-based packet-switching system with three phases of the packet transmission time. Each packet belongs to one of several priority classes, and the packets of each class arrive at a switch in a Poison process. The switch transmits queued packets on a priority basis with three phases of preemption mechanism. Namely, the transmission time of each packet consists of a preemptive-repeat part for the header, a preemptive-resume part for the information field, and a nonpreemptive part for the trailer. By an exact analysis of the associated queueing model, we obtain the Laplace-Stieltjes transform of the distribution function for the delay, i.e., the time from arrival to transmission completion, of a packet for each class. We derive a set of equations that calculates the mean response time for each class recursively. Based on this result, we plot the numerical values of the mean response times for several parameter settings. The probability generating function and the mean for the number of packets of each class present in the system at an arbitrary time are also given.

• Journal of KIISE:Information Networking
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• v.27 no.1
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• pp.22-29
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• 2000

In this paper, we analyzed the performance of EY-NPMA(Elimination Yield-Non-preemptive Priority Multiple Access) protocol-channel access control protocol of HIPERLAN(HIgh PErformance Radio Local Area Network) type 1 specification, adopted as european high speed wireless LAN standard by ETSI(European Telecommunication Standards Institute). We established a system model for EY-NPMA protocol analysis, analyzed success probability in a channel access cycle, and derived expressions for the average length of contention phase. Using a M/G/1 model, we approximated the normalized delay, and throughput, and we evaluated these results by simulations.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.225-229
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• 2017

In this paper, various units of industrial disaster safety threats as well as local and national facilities unit real-time detection and prevention refer to the corresponding system goes into disaster management preparedness, prevention, response recovery of phase I systematic ICT skills that can be managed more efficiently. In addition, the immediate disaster prevention and preparedness for early forecasting preemptive damage scale and high-tech information exchange technology to overcome the limitations of a human disaster in the field against the analysis and strategy of preemptive disaster safety management with smart risk management and prevention in response and recovery and the scene quickly and efficient mutual cooperation and effective collaboration and cooperation of the Community Center social security presented a smart disaster safety management system.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.193-201
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• 2014

In cognitive radio networks, the packet transmissions of the secondary users (SUs) can be interrupted randomly by the primary users (PUs). That is to say, the PU packets have preemptive priority over the SU packets. In order to enhance the quality of service (QoS) for the SUs, we propose a spectrum access strategy with an ${\alpha}$-Retry policy. A buffer is deployed for the SU packets. An interrupted SU packet will return to the buffer with probability ${\alpha}$ for later retrial, or leave the system with probability (1-${\alpha}$). For mathematical analysis, we build a preemptive priority queue and model the spectrum access strategy with an ${\alpha}$-Retry policy as a two-dimensional discrete-time Markov chain (DTMC).We give the transition probability matrix of the Markov chain and obtain the steady-state distribution. Accordingly, we derive the formulas for the blocked rate, the forced dropping rate, the throughput and the average delay of the SU packets. With numerical results, we show the influence of the retrial probability for the strategy proposed in this paper on different performance measures. Finally, based on the trade-off between different performance measures, we construct a cost function and optimize the retrial probabilities with respect to different system parameters by employing an iterative algorithm.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.6
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• pp.557-564
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• 2009

Welding residual stress is occurred after welding process. Tensile residual stress is one factor of PWSCC. Repair welding usually happened during the manufacturing welding process. Repair welds cause strong tensile residual stress. In PWR, Repair weldments made by Alloy 82/182 is susceptible to PWSCC caused by tensile stress, material and environment. Therefore, mitigation of welding residual stress in weldments is important for reliable operating. PWOL is one of the methods for mitigation and verified for over twenty years. In this paper, residual stress distribution of repaired weldments and the effect of PWOL on mitigation is examined for surge nozzle.