• Title/Summary/Keyword: on-line algorithms

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Buffer Management Algorithms in Unbounded Buffers

  • Kim, Jae-Hoon
    • Journal of information and communication convergence engineering
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    • v.8 no.6
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    • pp.721-724
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    • 2010
  • In a network router, packet loss may occur when it overflows due to sudden burst traffic. This paper studies how much large buffers are required to eliminate the packet losses. There are buffers on which packet arrive and one output port to which a packet is transmitted at a time. The buffer management algorithm should determine one of the buffers whose packet is transmitted to the output port at each time. The front packet belonging to the buffer determined by the algorithm is transmitted. The goal is to minimize the sum of the lengths of buffers to transmit all the packets. We provide an optimal off-line algorithm and also we show the lower bounds of on-line algorithms. The on-line algorithm has no prior information of the packets having arrived in the future. Its performance is compared to that of the optimal off-line algorithm.

Performance Assessments of Three Line Simplification Algorithms with Tolerance Changes (임계값 설정에 따른 선형 단순화 알고리듬의 반응 특성 연구)

  • Lee, Jae Eun;Park, Woo Jin;Yu, Ki Yun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.4
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    • pp.363-368
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    • 2012
  • The result of the line simplification algorithm varies with the choice of algorithms, the change in tolerance and the selection of target objects. Three of the algorithms used in this study are Sleeve-fitting, Visvalingam-Whyatt, and Bend-simplify. They were applied to the three kinds of objects which were buildings, rivers, and roads with the five degrees of the tolerance. Through this experiments the vector displacement, the areal displacement, and the angular displacement were measured and the qualitative analysis was performed with the trend line of the errors. The experimental results show that errors were differ from tolerance values, and characteristics of line simplification algorithms based on changes of tolerance were understood.

Resource Augmentation Analysis on Broadcast Scheduling for Requests with Deadlines (마감시간을 가진 요청들에 대한 브로드캐스트 스케줄링의 자원추가 분석)

  • Kim, Jae-hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.12
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    • pp.2981-2986
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    • 2015
  • In this paper, there are m servers to carry out broadcasts and the scheduling problem to serve the requests with deadlines is studied. If a server broadcasts a page, then all the requests which require the page are satisfied. A scheduling algorithm shall determine which pages are broadcasted on servers at a time. Its goal is to maximize the sum of weights of requests satisfied within their deadlines. The performance of an on-line algorithm is compared with that of the optimal off-line algorithm which can see all the inputs in advance. In general, the off-line algorithms outperform the on-line algorithms. So we will use the resource augmentation analysis in which the on-line algorithms can utilize more resources. We consider the case that the on-line algorithms can use more servers in this paper.

An On-line Algorithm for Machine Layout Problem (기계 배치 문제의 온라인 알고리즘)

  • Wang, Gi-Nam
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.6
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    • pp.27-36
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    • 1995
  • This paper covers algorithms to determine a machine assignment strategy to locations on a single straight track by minimizing the total backtrack distance. Three different algorithms ar presented: an efficient heuristic procedure, the branch-and-bound algorithm, and the nerual network approach. Simulation results show that the proposed algorithms have potential power to design an on-line optimizer.

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An On-line Scheduling Algorithm for a GRID System (GRID시스템을 위한 온라인 스케줄링 알고리즘)

  • 김학두;김진석;박형우
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.1_2
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    • pp.95-101
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    • 2004
  • The scheduling problem that maps independent tasks to heterogeneous resources in distributed computing systems is known as NP-complete[1]. GRID[2] is an example of distributed systems that consisted of heterogeneous resources. Many algorithms to solve this problem have been presented[1,3,4,5]. The scheduling algorithm can be classified into static scheduling algorithms and dynmic scheduling algorithms. A dynamic scheduling algorithm can be used when we can not predict the priority of tasks. Moreover, a dynamic scheduling algorithm can be divided into on-line mode algorithm and batch mode algorithm according to the scheduling time[1,6]. In this paper, we propose a new on-line mode scheduling algorithm. By extensive simulation, we can see that our scheduling algorithm outperforms previous scheduling algorithms.

Finding Rectilinear(L1), Link Metric, and Combined Shortest Paths with an Intelligent Search Method (지능형 최단 경로, 최소 꺾임 경로 및 혼합형 최단 경로 찾기)

  • Im, Jun-Sik
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.1
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    • pp.43-54
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    • 1996
  • This paper presents new heuristic search algorithms for searching rectilinear r(L1), link metric, and combined shortest paths in the presence of orthogonal obstacles. The GMD(GuidedMinimum Detour) algorithm combines the best features of maze-running algorithms and line-search algorithms. The SGMD(Line-by-Line GuidedMinimum Detour)algorithm is a modiffication of the GMD algorithm that improves efficiency using line-by-line extensions. Our GMD and LGMD algorithms always find a rectilinear shortest path using the guided A search method without constructing a connection graph that contains a shortest path. The GMD and the LGMD algorithms can be implemented in O(m+eloge+NlogN) and O(eloge+NlogN) time, respectively, and O(e+N) space, where m is the total number of searched nodes, is the number of boundary sides of obstacles, and N is the total number of searched line segment. Based on the LGMD algorithm, we consider not only the problems of finding a link metric shortest path in terms of the number of bends, but also the combined L1 metric and Link Metric shortest path in terms of the length and the number of bands.

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Design of PID adaptive control system combining Genetic Algorithms and Neural Network (유전알고리즘과 신경망을 결합한 PID 적응제어 시스템의 설계)

  • 조용갑;박재형;박윤명;서현재;최부귀
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.1
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    • pp.105-111
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    • 1999
  • This Paper is about how to deside the best parameter of PID controller, using Genetic Algorithms and Neural Networks. Control by Genetic Algorithms, which is off-line pass, has weakness for disturbance. So we want to improve like followings by adding Neural Network to controller and putting it on line. First we find PID parameter by Genetic Algorithms in forward pass of Neural Network and set the best output condition according to the increasing number of generation. Second, we explain the adaptability for disturbance with simulation by correcting parameter by backpropagation learning rule by using the learning ability of Neural Network.

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A Method for Quantitative Performance Evaluation of Edge Detection Algorithms Depending on Chosen Parameters that Influence the Performance of Edge Detection (경계선 검출 성능에 영향을 주는 변수 변화에 따른 경계선 검출 알고리듬 성능의 정량적인 평가 방법)

  • 양희성;김유호;한정현;이은석;이준호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.993-1001
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    • 2000
  • This research features a method that quantitatively evaluates the performance of edge detection algorithms. Contrary to conventional methods that evaluate the performance of edge detection as a function of the amount of noise added to he input image, the proposed method is capable of assessing the performance of edge detection algorithms based on chosen parameters that influence the performance of edge detection. We have proposed a quantitative measure, called average performance index, that compares the average performance of different edge detection algorithms. We have applied the method to the commonly used edge detectors, Sobel, LOG(Laplacian of Gaussian), and Canny edge detectors for noisy images that contain straight line edges and curved line edges. Two kinds of noises i.e, Gaussian and impulse noises, are used. Experimental results show that our method of quantitatively evaluating the performance of edge detection algorithms can facilitate the selection of the optimal dge detection algorithm for a given task.

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Scheduling Algorithm to Minimize Total Error for Imprecise On-Line Tasks

  • Song, Gi-Hyeon
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1741-1751
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    • 2007
  • The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

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