• 정보처리학회논문지A
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• 제11A권7호
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• pp.511-520
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• 2004

P2P(peer-to-peer) 모델은 클라이언트-서버 모델의 서버 링크 병목현상을 해결하기 위한 대안으로 고려되고 있다. 본 연구에서, 우리는 P2P 네트웍에서 연속형 미디어의 배포 문제 중 두 가지를 다루었다. 첫째는 다중-소스 스트리밍 세션을 위한 미디어 데이터의 전송 스케쥴링 문제이다. 버퍼링 지연을 최소화시키는 정교한 분산 전송 스케쥴링으로서FSS(fixed-length slotted scheduling)라는 기법을 제안한다. 두 번째 문제는 스스로 성장하는 P2P 시스템에서 미디어 컨텐츠의 배포 속도 향상 문제이다. 이를 위해 우리는 시스템의 스트리밍 용량이 증가하는 속도를 가속시키는 FAST라 불리는 기술을 제안한다.

• 대한산업공학회지
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• 제21권1호
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• pp.119-135
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• 1995

We consider problems of tool loading and scheduling in a flexible manufacturing system (FMS) in which tool transportation constitutes the major portion of material flows. In this type of FMSs, parts are initially assigned to machines and released to the machines according to input sequencing rules. Operations for the parts released to the machines are performed by tools initially loaded onto the machines or provided by an automatic tool transport robot when needed. For an efficient operation of such systems, therefore, we may have to consider loading and scheduling problems for tools in addition to those for parts. In this paper, we consider three problems, part loading, tool loading, and tool scheduling problems with the overall objective of minimizing the makespan. The part loading problem is solved by a method similar to that for the bin packing problem and then a heuristic based on the frequency of tool usage is applied for tool loading. Also suggested are part input sequencing and tool scheduling rules. To show the effectiveness of the overall algorithm suggested here, we compare it with an existing algorithm through a series of computational tests on randomly generated test problems.

• 한국시뮬레이션학회논문지
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• 제15권3호
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• pp.31-37
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• 2006

모바일 그리드 네트워크의 단점인 연결의 불안정성과 이기종의 비전용 이동장비의 사용을 고려한 환경에서, 모바일 그리드 시스템의 효율적인 성능을 제공하기 위해서 본 논문에서는 작업할당 스케줄링 알고리즘을 제시하였다. 제시한 스케줄링 알고리즘은 두 개의 중요기능이 있으며, 이는 작업처리 시간을 예측하는 것과 작업을 수행시키기 위해 필요한 최적의 이동단말기의 개수를 정하는 것이다. 이러한 성능을 제공하기 위해서 제시한 알고리즘에서는 무선 네트워크 환경에서 이기종의 비전용장비의 영향을 고려한 네트워크의 지연시간을 계산하는 수학적인 수식을 제시하였다. 또한 구현된 모바일 그리드 환경에서 분산 어플리케이션을 수행하여 제시한 스케줄링 알고리즘에 대해 성능평가를 수행하였다.

• 한국CDE학회논문집
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• 제17권1호
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• pp.26-34
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• 2012

Assembly scheduling in shipbuilding is responsible for determine assembly process orders and departmental production schedule for the block, the basic composite unit of ships. It is necessary much more information to decide production scheduling as the characteristic of shipbuilding which has been more complex and more various and also, a lot of waste of time and of human power is generated in the course of data processing. The target shipbuilding manufacturer of this study use empirical techniques, based on the user's discretion, to compile and to apply data which are scattered in DB storages separately. Because of that reason, the user should not only be performed identification and screening operations but also modification and verification for vast amounts of data, so it is hard to keep the consistency of the data and also the operation time is not constant. Accordingly, the object in this study is by presenting an efficient DB framework to reduce wasting time and man-hour at experienced-oriented process, abate user's manual operations and support an efficient scheduling in assembly processes.

• 한국멀티미디어학회논문지
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• 제9권1호
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• pp.119-126
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• 2006

멀티 프로세서 시스템에서 스케쥴링은 매우 중요한 부분이지만, 최적의 해를 구하는 것이 복잡하여 최근 다양한 휴리스틱 방법들에 의한 스케쥴링 알고리즘들이 제안되고 있다. 본 논문에서는 유전 알고리즘을 이용한 새로운 스케쥴링 알고리즘을 제시한다. 또한, 해를 구하는 과정에서 시뮬레이티드 어닐링 (simulated annealing)의 확률을 이용하여 유전 알고리즘의 성능을 개선시킨다. 제시된 알고리즘은 태스크들의 최종 수행 완료 시간 (makespan)을 최소화하는 것을 목표로 한다. 모의 실험을 통하여 제시된 알고리즘이 다른 알고리즘보다 최종 수행 완료 시간이 작음을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4988-5012
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• 2019

As a subset of the Internet of Things, the Internet of Energy (IoE) is expected to tackle the problems faced by the current smart grid framework. Notably, the conventional day-ahead power scheduling of the smart grid should be redesigned in the IoE architecture to take into consideration the intermittence of scattered renewable generations, large amounts of power consumption data, and the uncertainty of the arrival time of electric vehicles (EVs). Accordingly, a day-ahead power scheduling system for the future IoE is proposed in this research to maximize the usage of distributed renewables and reduce carbon emission caused by the traditional power generation. Meanwhile, flexible charging mechanism of EVs is employed to provide preferred charging options for moving EVs and flatten the load profile simultaneously. The simulation results revealed that the proposed power scheduling mechanism not only achieves emission reduction and balances power load and supply effectively, but also fits each individual EV user's preference.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• 한국멀티미디어학회논문지
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• 제3권3호
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• pp.309-319
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• 2000

병렬 스케줄링의 목적은 다중프로세서 시스템 환경에서 병렬성을 가진 응용프로그램에 대해 최소의 동기화 오버헤드와 부하균등(load balance)을 달성하도록 스케줄링을 수행하는데 있다. 프로세서들이 병렬 반복(iteration)을 실행하기 위해서는 메모리로부터 반복들에 대한 chunk를 계산하고 할당받게 된다. 이때, 전역 메모리의 상호 배타적인 빈번한 접근으로 많은 스케쥴링 오버헤드 및 병목현상이 발생된다. 또한, 프로세서에게 할당된 chunk내 병렬 반복들의 분포가 서로 상이한 경우,각 chunk의 실행시간이 서로 달라 부하불균등의 원인이 되어 결과적으로 전체 스케쥴링 성능에 나쁜 영향을 준다. 따라서, 최소의 스케줄링 오버 헤드와 부하균등을 달성하기 위해 본 논문에 서는 기존의 방법들에서 문제점들을 도출하고, 자료의 국부성과 프로세서 동족성(affinity)을 고려한 병렬 루프 스케줄링 알고리즘을 제안한다.

• Journal of Computing Science and Engineering
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• 제8권1호
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• pp.43-56
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• 2014

Semi-partitioned scheduling is a new approach for allocating tasks on multiprocessor platforms. By splitting some tasks between processors, semi-partitioned scheduling is used to improve processor utilization. In this paper, a new semi-partitioned scheduling algorithm called SS-DRM is proposed for multiprocessor platforms. The scheduling policy used in SS-DRM is based on the delayed rate monotonic algorithm, which is a modified version of the rate monotonic algorithm that can achieve higher processor utilization. This algorithm can safely schedule any system composed of two tasks with total utilization less than or equal to that on a single processor. First, it is formally proven that any task which is feasible under the rate monotonic algorithm will be feasible under the delayed rate monotonic algorithm as well. Then, the existing allocation method is extended to the delayed rate monotonic algorithm. After that, two improvements are proposed to achieve more processor utilization with the SS-DRM algorithm than with the rate monotonic algorithm. According to the simulation results, SS-DRM improves the scheduling performance compared with previous work in terms of processor utilization, the number of required processors, and the number of created subtasks.