• Journal of Communications and Networks
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• 제14권6호
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• pp.692-702
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• 2012

Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: Priority assignment and resource allocation. Different service-type connections primarily depend on their QoS requirements to adjust priority assignments and dispatch bandwidth resources dynamically. We consider both starvation avoidance and resource management. Simulation results show that our APDS methodology outperforms the representative scheduling approaches in QoS satisfaction and maintains fairness in starvation prevention.

• Journal of Communications and Networks
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• 제8권3호
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• pp.297-305
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• 2006

High-rate wireless personal area network (HR-WPAN) has been standardized by the IEEE 802.15.3 task group (TG). To support multimedia services, the IEEE 802.15.3 TG adopts a time-slotted medium access control (MAC) protocol controlled by a central device. In the time division multiple access (TDMA)-based wireless packet networks, the packet scheduling algorithm plays a key role in quality of service (QoS) provisioning for multimedia services. In this paper, we propose an adaptive cross-layer packet scheduling method for the TDMA-based HR-WPAN. Physical channel conditions, MAC protocol, link layer status, random traffic arrival, and QoS requirement are taken into consideration by the proposed packet scheduling method. Performance evaluations are carried out through extensive simulations and significant performance enhancements are observed. Furthermore, the performance of the proposed scheme remains stable regardless of the variable system parameters such as the number of devices (DEVs) and delay bound.

• Industrial Engineering and Management Systems
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• 제13권1호
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• pp.43-51
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• 2014

This study presents an application of adaptive particle swarm optimization (APSO) to solving the bi-level job-shop scheduling problem (JSP). The test problem presented here is $10{\times}10$ JSP (ten jobs and ten machines) with tribottleneck machines formulated as a bi-level formulation. APSO is used to solve the test problem and the result is compared with the result solved by basic PSO. The results of the test problem show that the results from APSO are significantly different when compared with the result from basic PSO in terms of the upper level objective value and the iteration number in which the best solution is first identified, but there is no significant difference in the lower objective value. These results confirmed that the quality of solutions from APSO is better than the basic PSO. Moreover, APSO can be used directly on a new problem instance without the exercise to select parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.234-234
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• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer takes an adaptive scheduling gains where motet speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimated values of stator resistance and speed are included as observer parameters. The parameters of the PI controllers adopted in the adaptive law for the estimation of stator resistance and motor speed are determined by simple genetic algorithm. Simulation results in low speed region are given for comparison between proposed and conventional flux estimate scheme.

• 한국시뮬레이션학회논문지
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• 제19권3호
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• pp.45-54
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• 2010

반도체 제조공정에 내재된 복잡성은 작업일정(job scheduling) 문제를 해석적 방법으로는 풀기 어렵기 때문에 보통 시스템 파라미터의 변화에 대한 효과를 이산사건 모델링 시뮬레이션에 의존하여 왔다. 한편 장비 고장 등 예측 불가능한 사건들은 고정된 작업일정 기법을 사용할 경우 전체 공정의 효율을 악화시킨다. 따라서 이러한 불확실성에 대해 최적의 성능을 내기 위해서는 작업일정을 실시간으로 대처 변경하는 것이 필요하다. 본 논문은 반도체 제조 공정에 대해 시스템 제어관점의 접근방법을 적용하여 이 문제에 적응형 실시간 작업제어 틀을 제안하고, DEVS 모델링 시뮬레이션 환경을 기반으로 제안된 틀을 설계 구현하였다. 제안된 방법은 기존의 임기응변적인 소프트웨어적인 방법에 비추어볼 때 전체 시스템을 이해하기 쉬우면서도 또한 추가되는 작업제어 규칙도 쉽게 추가 적용할 수 있는 유연성을 장점으로 가지고 있다. 여러 가지 실험결과 제안된 적응형 실시간 작업제어 프레임워크는 고정 작업규칙 방법에 비해 훨씬 나은 결과를 보여주어 그 효용성을 입증하였다.

• 컴퓨터교육학회논문지
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• 제14권2호
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• pp.75-82
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• 2011

클라우드 컴퓨팅은 인터넷 혹은 인트라넷 기반의 대규모 컴퓨팅 자원을 가상화하여 사용자가 원하는 서비스를 언제 어디서든 제공하도록 하는 컴퓨팅 패러다임이다. 이러한 클라우드 컴퓨팅은 시스템 환경 자체가 대규모의 데이터를 처리하며, 다중 사용자 접속 환경 기반이어서 시스템의 신뢰성이 중요한 요소이다. 본 논문에서는 클라우드 환경에서 발생하는 문제(사용자의 요구사항 변경, 자원 결함 발생 등)를 해결하기 위해 시스템 환경 내부의 자원 변화에 대처할 수 있고 결함 포용적인 신뢰성 기반 적응적 스케줄링 기법을 제안한다. 이 기법의 타당성을 검증하기 위해 CloudSim 시뮬레이션 환경에서 실험하였다.

• 한국멀티미디어학회논문지
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• 제20권9호
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.843-859
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• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

• 한국컴퓨터산업학회논문지
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• 제6권2호
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• pp.233-240
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• 2005

유비쿼터스 컴퓨팅이 소개된 이후로 컴퓨팅 환경에 대한 관점이 변화하고 있다. 유비쿼터스 컴퓨팅에서 사용자가 원하는 서비스를 제공하기 위해서는 상환 정보가 필요하다. 스케줄 관리 시스템은 이러한 상황 정보가 매우 필요한 분야이다. 그러나, 기존의 스케줄 관리 시스템에서는 다양한 상황 정보를 고려하지 않고 있다. 이를 극복하고자, 본 논문에서는 각 사용자의 다양한 상황을 고려한 상황 적응적인 새로운 웹 기반 스케줄 관리 시스템을 설계하고 구현한다. 이를 위해 시스템을 설계하고, 사용자, 시간, 계절, 위치 상황에 이를 적용하여 각 사용자에게 적합한 스케줄을 제공함을 구현결과를 통해 보였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1074-1077
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• 2002

This paper proposes an adaptive pricing system with scheduling to balance the demand for contents and to realize an effective use of resources in contents delivery networks. In the proposed adaptive pricing system, the table of the service levels and prices (tariff) is shown to each user at the start of service and each user chooses one of the service classes. These prices are decided adaptively reflecting the congestion state of the networks. Then, by the proposed scheduling algorithm, these requests are scheduled so as to keep the service level agreements completely.