• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1B
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• pp.11-17
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• 2003

In this paper, we presented the dynamic random access channel allocation method under the priority based scheduling policy in order to improve the system performance of HIPERLAN/2 standardized by ETSI According to the scheduling policy, AP scheduler primarily allocates the resource to the collision MT This scheduling policy bring about decreasing the transmission delay of collision MT Dynamic RCH(random access channel) allocation method decreases the collision probability by increasing the number of RCH slots in case of low traffic. While it increases the maximum throughput by increasing the number of the data transmission slots in case of high traffic Therefore dynamic allocation method of RCH slots decreases the scheduling delay and increases the throughput When we evaluate the performance of presented method based on standards, we saw that the presented method improve the performance of the MAC protocol in terms of throughput and transmission delay.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.2
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• pp.45-54
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• 2008

In this paper, a dynamic GTS scheduling method based on IEEE 802.15.4 is proposed for wireless control system. The proposed method can guarantee a transmission of real-time periodic and sporadic data within the time frame in factory environment. The modified superframe of IEEE 802.15.4 was used to the dynamic scheduling method of real-time mixed traffic(periodic data, sporadic data, and non real-time message). By separating CFP and CAP properly, the sporadic and non real-time messages are transmitted effectively and guarantee real-time transmission within a deadline. The simulation results show the improvement of real-time performance of periodic and sporadic data.

• 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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.269-279
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• 1999

본 연구는 Web상에서 원격 협력 학습을 위한 수준별 학습자 모집 스케줄링 에이전트의 설계와 구현에 관해 제안한다. 본 시스템의 구조는 원격 교사 모듈과 여러 명의 학습자, 그리고 이를 연결해 주는 스케줄링 Agents, 학습자를 진단할 수 있는 진단 Agent로 구성된다. 컴퓨터가 분산환경으로 발전됨에 따라서 교육의 변화도 가속화되었고, 지식의 공유와 정보의 공유가 원격 협력학습에 의하여 절실히 필요하게 되었다. 원격 협력 학습에서의 학습자는 동일한 과목과 주제에 흥미를 느끼는 여러 명의 아동이 동시에 학습할 수 있는 상황이 필요하며, 선행 지식 또한 비슷한 수준이어야 동일한 주제로 학습의 효과가 있다. 이런 학습자를 판단하기 위해서 진단 Agent가 학습자를 진단하며 스케줄링 Agents의 학습자 지식에 추가한 후 스케줄링 Agents가 학습자의 기본 사항과 요구 내용을 추론하여 비슷한 수준의 학습자를 연결한다. 교사 모듈은 전통적인 ITS의 구조의 교수 학습 모듈, 전문가모듈로 구성되어 교수 학습을 할 수 있다. 이렇게 여러 명의 학습자를 연결하여 협력학습을 하기 위해서는 학습자간의 요구사항과 지식 수준 그리고 학습 가능한 시간이 같아야 하는데 이를 위해 시간을 자원으로 하는 동적 자원 스케줄링(Dynamic Resource Scheduling)으로 모델링 하였다. 본 연구에서 도형학습을 기반으로 하는 실험을 통해 구현한 원격 협력학습을 위한 지능형 스케줄링 에이전트를 평가하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1302-1320
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• 2015

In cloud, everything can be provided as a service wherein a large number of users submit their jobs and wait for their services. hus, scheduling plays major role for providing the resources efficiently to the submitted jobs. The brainwave of the proposed ork is to improve user satisfaction, to balance the load efficiently and to bolster the resource utilization. Hence, this paper roposes an Adaptive Multilevel Scheduling System (AMSS) which will process the jobs in a multileveled fashion. The first level ontains Preprocessing Jobs with Multi-Criteria (PJMC) which will preprocess the jobs to elevate the user satisfaction and to itigate the jobs violation. In the second level, a Deadline Based Dynamic Priority Scheduler (DBDPS) is proposed which will ynamically prioritize the jobs for evading starvation. At the third level, Contest Mapping Jobs with Virtual Machine (CMJVM) is roposed that will map the job to suitable Virtual Machine (VM). In the last level, VM Scheduler is introduced in the two-tier VM rchitecture that will efficiently schedule the jobs and increase the resource utilization. These contributions will mitigate job iolations, avoid starvation, increase throughput and maximize resource utilization. Experimental results show that the performance f AMSS is better than other algorithms.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.484-491
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• 2003

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1A
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• pp.24-33
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• 2007

In this paper, two different dynamic cell coordination strategies for frequency flat and selective fading are proposed for efficient subcarrier allocation in the joint consideration of adaptive modulation and variable frequency reuse in the channel-aware OFDMA downlink multicellular environment. Compared to a conventional OFDMA system without cell coordination, where system throughput may become degraded due to the persistent interference from other cells, the proposed system dynamically allows RNC to apply different reuse factors on each subchannel and scheduling in consideration of channel and interference conditions of individual users so as to increase the system throughput and guarantee QoS of each user. In a frequency flat fading, the dynamic scheme with the proposed scheduling achieves on average three times larger throughput than the conventional dynamic scheme [8]. In a selective fading channel, the proposed schemes showed 2.6 times as large throughput as that of a single reuse factor of one for all subchannels.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.93-99
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• 1997

Most of the past studies on FMS scheduling problems may be classified into two classes, namely off-line scheduling and on-line scheduling approach. The off-line scheduling methods are used mostly for FMS planning purposes and may not be useful real time control of FMSs, because it generates solutions only after a relatively long period of time. The on-line scheduling methods are used extensively for dynamic real-time control of FMSs although the performance of on-line scheduling algorithms tends vary dramatically depending on various configurations of FMS. Current study is about finding a better on-line scheduling rules for FMS operations. In this study, we propose a method to create priority functions that can be used in setting relative priorities among jobs or machines in on-line scheduling. The priority functions reflect the configuration of FMS and the user-defined objective functions. The priority functions are generated from diverse dispatching rules which may be considered a special priority functions by themselves, and used to determine the order of processing and transporting parts. Overall system of our work consists of two modules, the Priority Function Evolution Module (PFEM) and the FMS Simulation Module (FMSSM). The PFEM generates new priority functions using input variables from a terminal set and primitive functions from a function set by genetic programming. And the FMSSM evaluates each priority function by a simulation methodology. Based on these evaluated values, the PFEM creates new priority functions by using crossover, mutation operation and probabilistic selection. These processes are iteratively applied until the termination criteria are satisfied. We considered various configurations and objective functions of FMSs in our study, and we seek a workable solution rather than an optimum or near optimum solution in scheduling FMS operations in real time. To verify the viability of our approach, experimental results of our model on real FMS are included.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.161-178
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• 1994

FMS are being installed to improve productivity, manufacturing consistency and flexibility. However, FMS are quite expensive and efforts must be made to avoid the high investment risk. The objective of this paper is to enable the real-time rescheduling under dynamic changes in FMS environment. For this purpose, a KBSS (Knowledge-Based Scheduling System) in FMS environment is developed. This KBSS will meet various requirements of users, for example, to minimize makespan, average flow time, or to maximize machine utilization.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.237-244
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• 2013

We propose Energy-constrained Multiprocessor Real-Time Scheduling algorithms for (m,k)-firm deadline constrained tasks (EMRTS-MK). Rather than simply saving as much energy as possible, we consider energy as hard constraint under which the system remains functional and delivers an acceptable performance at least during the prescribed mission time. We evaluate EMRTS-MKs in several experiments, which quantitatively show that they achieve the scheduling objectives.