• Title/Summary/Keyword: tree search algorithm

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Binary Search Tree with Switch Pointers for IP Address Lookup (스위치 포인터를 이용한 균형 이진 IP 주소 검색 구조)

  • Kim, Hyeong-Gee;Lim, Hye-Sook
    • Journal of KIISE:Information Networking
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    • v.36 no.1
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    • pp.57-67
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    • 2009
  • Packet forwarding in the Internet routers is to find out the longest prefix that matches the destination address of an input packet and to forward the input packet to the output port designated by the longest matched prefix. The IP address lookup is the key of the packet forwarding, and it is required to have efficient data structures and search algorithms to provide the high-speed lookup performance. In this paper, an efficient IP address lookup algorithm using binary search is investigated. Most of the existing binary search algorithms are not efficient in search performance since they do not provide a balanced search. The proposed binary search algorithm performs perfectly balanced binary search using switch pointers. The performance of the proposed algorithm is evaluated using actual backbone routing data and it is shown that the proposed algorithm provides very good search performance without increasing the memory amount storing the forwarding table. The proposed algorithm also provides very good scalability since it can be easily extended for multi-way search and for large forwarding tables

A search mechanism for moving objects in a spatial database (공간 데이타베이스에서 이동 객체의 탐색기법)

  • 유병구;황수찬;백중환
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.1
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    • pp.25-33
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    • 1998
  • This paepr presents an algorithm for searching an object in a fast way which contains a continuous moving object in multi-dimensional spatical databases. This algorithm improves the search method of R-tree for the case that a target object is continuously moving in a spatial database. It starts the searching from the current node instead of the root of R-tree. Thus, the algorithm will find the target object from the entries of current node or sibling nodes in the most cases. The performance analysis shows that it is more efficient than the existing algorithm for R-tree when search windows or target objects are continuously moving.

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Tabu Search-Genetic Process Mining Algorithm for Discovering Stochastic Process Tree (확률적 프로세스 트리 생성을 위한 타부 검색 -유전자 프로세스 마이닝 알고리즘)

  • Joo, Woo-Min;Choi, Jin Young
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.183-193
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    • 2019
  • Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

AN OPTIMAL ALGORITHM FOR FINDING DETH-FIRST SPANNING TREE ON PERMUTATION GRAPHS

  • Mondal, Sukumar;Pal, Madhumangal;Pal, Tapan K.
    • Journal of applied mathematics & informatics
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    • v.6 no.3
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    • pp.727-734
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    • 1999
  • Let G be a connected graph of n vertices. The problem of finding a depth-first spanning tree of G is to find a connected subgraph of G with the n vertices and n-1 edges by depth-first-search. in this paper we propose an O(n) time algorithm to solve this problem on permutation graphs.

DGR-Tree : An Efficient Index Structure for POI Search in Ubiquitous Location Based Services (DGR-Tree : u-LBS에서 POI의 검색을 위한 효율적인 인덱스 구조)

  • Lee, Deuk-Woo;Kang, Hong-Koo;Lee, Ki-Young;Han, Ki-Joon
    • Journal of Korea Spatial Information System Society
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    • v.11 no.3
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    • pp.55-62
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    • 2009
  • Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

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Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion (효율적인 노드 삽입을 이용한 순서화된 병렬 트리-탐색 기반 저복잡도 연판정 다중 안테나 검출 알고리즘)

  • Kim, Kilhwan;Park, Jangyong;Kim, Jaeseok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37A no.10
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    • pp.841-849
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    • 2012
  • This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a $4{\times}4$ system, the proposed algorithm shows a performance degradation of less than 0.1dB.

An Efficient k-D tree Traversal Algorithm for Ray Tracing on a GPU (GPU상에서 동작하는 Ray Tracing을 위한 효과적인 k-D tree 탐색 알고리즘)

  • Kang, Yoon-Sig;Park, Woo-Chan;Seo, Choong-Won;Yang, Sung-Bong
    • Journal of KIISE:Computer Systems and Theory
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    • v.35 no.3
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    • pp.133-140
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    • 2008
  • This paper proposes an effective k-D tree traversal algorithm for ray tracing on a GPU. The previous k-D tree traverse algorithm based on GPU uses bottom-up searching from a leaf to the root after failing to find the ray intersected primitive in the leaf node. During the bottom-up search the algorithm decides the current node is visited or not from the parent node. In such a way, we need to visit the parent node which was already visited and the duplicated bounding box intersection tests. The new k-D tree traverse algorithm reduces the brother and parent duplicated visit by using an efficient method which decides whether the brother node is already visited or not during the bottom-up search. Also the algorithm take place bounding box intersection tests only for the nodes which is not yet done. As a result our experiment shows the new algorithm is about 30% faster than the previous.

Efficient Multi-way Tree Search Algorithm for Huffman Decoder

  • Cha, Hyungtai;Woo, Kwanghee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.34-39
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    • 2004
  • Huffman coding which has been used in many data compression algorithms is a popular data compression technique used to reduce statistical redundancy of a signal. It has been proposed that the Huffman algorithm can decode efficiently using characteristics of the Huffman tables and patterns of the Huffman codeword. We propose a new Huffman decoding algorithm which used a multi way tree search and present an efficient hardware implementation method. This algorithm has a small logic area and memory space and is optimized for high speed decoding. The proposed Huffman decoding algorithm can be applied for many multimedia systems such as MPEG audio decoder.

Implementation of Artificial Intelligence Computer Go Program Using a Convolutional Neural Network and Monte Carlo Tree Search (Convolutional Neural Network와 Monte Carlo Tree Search를 이용한 인공지능 바둑 프로그램의 구현)

  • Ki, Cheol-min;Cho, Tai-Hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.405-408
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    • 2016
  • Games like Go, Chess, Janggi have helped to brain development of the people. These games are developed by computer program. And many algorithms have been developed to allow myself to play. The person winning chess program was developed in the 1990s. But game of go is too large number of cases. So it was considered impossible to win professional go player. However, with the use of MCTS(Monte Carlo Tree Search) and CNN(Convolutional Neural Network), the performance of the go algorithm is greatly improved. In this paper, using CNN and MCTS were proceeding development of go algorithm. Using the manual of go learning CNN look for the best position, MCTS calculates the win probability in the game to proceed with simulation. In addition, extract pattern information of go using existing manual of go, plans to improve speed and performance by using it. This method is showed a better performance than general go algorithm. Also if it is receiving sufficient computing power, it seems to be even more improved performance.

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Design and Implementation of a Genetic Algorithm for Global Routing (글로벌 라우팅 유전자 알고리즘의 설계와 구현)

  • 송호정;송기용
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.2
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    • pp.89-95
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    • 2002
  • Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

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