• 제목/요약/키워드: Search algorithms

검색결과 1,328건 처리시간 0.031초

Packet Classification Using Two-Dimensional Binary Search on Length (길이에 대한 2차원 이진검색을 이용한 패킷분류 구조)

  • Mun, Ju-Hyoung;Lim, Hye-Sook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제32권9B호
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    • pp.577-588
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    • 2007
  • The rapid growth of the Internet has stimulated the development of various new applications and services, and the service providers and the Internet users now require different levels of service qualities rather than current best-effort service which treats all incoming packet equally. Therefore, next generation routers should provide the various levels of services. In order to provide the quality of services, incoming packets should be classified into flows according to pre-defined rules, and this should be performed for all incoming packets in wire-speed. Packet classification not only involves multi-dimensional search but also finds the highest priority rule among all matching rules. Area-based quad-trie is a very good algorithm that constructs a two-dimensional trie using source and destination prefix fields. However, it performs the linear search for the prefix length, and hence it does not show very good search performance. In this paper, we propose to apply binary search on length to the area-based quad-trie algorithm. In improving the search performance, we also propose two new algorithms considering the priority of rules in building the trie.

Blade Shape Optimization of Wind Turbines Using Genetic Algorithms and Pattern Search Method (유전자 알고리즘 및 패턴 서치 방법을 이용한 풍력 터빈 블레이드의 형상 최적화)

  • Yi, Jin-Hak;Sale, Danny
    • KSCE Journal of Civil and Environmental Engineering Research
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    • 제32권6A호
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    • pp.369-378
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    • 2012
  • In this study, direct-search based optimization methods are applied for blade shape optimization of wind turbines and the optimization performances of several methods including conventional genetic algorithm, micro genetic algorithm and pattern search method are compared to propose a more efficient method. For this purpose, the currently available version of HARP_Opt (Horizontal Axis Rotor Performance Optimizer) code is enhanced to rationally evaluate the annual energy production value according to control strategies and to optimize the blade shape using pattern search method as well as genetic algorithm. The enhanced HARP_Opt code is applied to obtain the optimal turbine blade shape for 1MW class wind turbines. The results from pattern search method are compared with the results from conventional genetic algorithm and also micro genetic algorithm and it is found that the pattern search method has a better performance in achieving higher annual energy production and consistent optimal shapes and the micro genetic algorithm is better for reducing the calculation time.

Modified 3-step Search Motion Estimation Algorithm for Effective Early Termination (효과적인 조기 중단 기법을 위한 변형된 3단계 탐색 움직임 추정 알고리즘)

  • Yang, Hyeon-Cheol;Lee, Seong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • 제47권7호
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    • pp.70-77
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    • 2010
  • Motion estimation occupies most of the required computation in video compression, and many fast search algorithms were propsoed to reduce huge computation. SAD (sum-of-absolute difference) calculation is the most computation-intensive process in the motion estimation. Early termination is widely used in SAD calculation, where SAD calculation is terminated and it proceeds to next search position if partial SAD during SAD calculation exceeds current minimum SAD. In this paper, we proposed a modified 3-step search algorithm for effective early termination where only search order of search positions are adaptive rearranged. Simulation results show that the proposed motion estimation algorithm reduces computation by 17~30% over conventional 3-step search algorithm without extra computation, while maintaining same performance.

Fast Motion Estimation Technique using Efficient Prediction of Motion Vectors (움직임 벡터의 효율적 예측을 이용한 고속 움직임 추정 기법)

  • Kim, Jongho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.945-949
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    • 2009
  • This paper proposes an enhanced motion estimation that is one of core parts affecting the coding performance and visual quality in video coding. Although the full search technique, which is the most basic method of the motion estimation, presents the best visual quality, its computational complexity is great, since the search procedures to find the best matched block with each block in the current frame are carried out for all points inside the search area. Thus, various fast algorithms to reduce the computational complexity and maintain good visual quality have been proposed. The PMVFAST adopted the MPEG-4 visual standard produces the visual quality near that by the full search technique with the reduced computational complexity. In this paper, we propose a new motion vector prediction method using median processing. The proposed method reduces the computational complexity for the motion estimation significantly. Experimental results show that the proposed algorithm is faster than the PMVFAST and better than the full search in terms of search speed and average PSNR, respectively.

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A search-based high resolution frequency estimation providing improved convergence characteristics in power system (전력계통에서 수렴성 향상을 위한 탐색기반 고분해능 주파수 추정기법)

  • An, Gi-Sung;Seo, Young-Duk;Chang, Tae-Gyu;Kang, Sang-Hee
    • Journal of IKEEE
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    • 제22권4호
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    • pp.999-1005
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    • 2018
  • This paper proposed a search-based high resolution frequency estimation method in power systme. The proposed frequency estimation method adopts a slope-based adaptive search as a base of adaptive estimation structure. The architectural and operational parameters in this adaptive algorithm are changed using the information from context layer analysis of the signals including a localized full-search of spectral peak. The convergence rate of the proposed algorithm becomes much faster than those of other conventional slope-based adaptive algorithms by effectively reducing search range with the application of the localized full-search of spectrum peak. The improvements in accuracy and convergence rate of the proposed algorithm are confirmed through the performance comparison with other representative frequency estimation methods, such as, DFT(discrete Fourier transform) method, ECKF(extended complex Kalman filter), and MV(minimum variable) method.

Fast Motion Estimation Algorithms Through Adaptive Application of the Hadamard Transform (하다마드 변환의 적응적 적용을 이용한 고속 움직임 예측 알고리즘)

  • Lee, Hyuk;Kim, Jong-Ho;Jin, Soon-Jong;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제32권8C호
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    • pp.712-719
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    • 2007
  • In this paper, we propose a new, effective, fast motion estimation algorithms using $4{\times}4$ pixels Hadamard transform. The Hadamard transform has the advantage of simplicity because it uses only addition and subtraction. Motion estimation is composed of three stages. First, it should be decided whether to terminate the search early and use a previous motion vector with DC(Direct Current) coefficients. Then the adaptive matching scan order for motion estimation should be determined according to the image complexity using AC(Alternating Current) coefficients. Experimentally, we adapted this algorithms to MVFAST and PMVFAST algorithms, and the proposed algorithms turn out to be very efficient in terms of computational speed while remaining almost the same in terms of PSNR(Peak Signal-to-Noise Ratio) compared to MVFAST and PMVFAST algorithms.

Smallest-Small-World Cellular Genetic Algorithms (최소좁은세상 셀룰러 유전알고리즘)

  • Kang, Tae-Won
    • Journal of KIISE:Software and Applications
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    • 제34권11호
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    • pp.971-983
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    • 2007
  • Cellular Genetic Algorithms(CGAs) are a subclass of Genetic Algorithms(GAs) in which each individuals are placed in a given geographical distribution. In general, CGAs# population space is a regular network that has relatively long characteristic path length and high clustering coefficient in the view of the Networks Theory. Long average path length makes the genetic interaction of remote nodes slow. If we have the population#s path length shorter with keeping the high clustering coefficient value, CGAs# population space will converge faster without loss of diversity. In this paper, we propose Smallest-Small-World Cellular Genetic Algorithms(SSWCGAs). In SSWCGAs, each individual lives in a population space that is highly clustered but having shorter characteristic path length, so that the SSWCGAs promote exploration of the search space with no loss of exploitation tendency that comes from being clustered. Some experiments along with four real variable functions and two GA-hard problems show that the SSWCGAs are more effective than SGAs and CGAs.

Design Blockchain as a Service and Smart Contract with Secure Top-k Search that Improved Accuracy (정확도가 향상된 안전한 Top-k 검색 기반 서비스형 블록체인과 스마트 컨트랙트 설계)

  • Hobin Jang;Ji Young Chun;Ik Rae Jeong;Geontae Noh
    • Journal of Internet Computing and Services
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    • 제24권5호
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    • pp.85-96
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    • 2023
  • With advance of cloud computing technology, Blockchain as a Service of Cloud Service Provider has been utilized in various areas such as e-Commerce and financial companies to manage customer history and distribution history. However, if users' search history, purchase history, etc. are to be utilized in a BaaS in areas such as recommendation algorithms and search engine development, the users' search queries will be exposed to the company operating the BaaS, and privacy issues will be occured. Z. Guan et al. ensure the unlinkability between users' search query and search result using searchable encryption, and based on the inner product similarity, they select Top-k results that are highly relevant to the users' search query. However, there is a problem that the Top-k results selection may be not possible due to ties of inner product similarity, and BaaS over cloud is not considered. Therefore, this paper solve the problem of Z. Guan et al. using cosine similarity, so we improve accuracy of search result. And based on this, we design a BaaS with secure Top-k search that improved accuracy. Furthermore, we design a smart contracts that preserve privacy of users' search and obtain Top-k search results that are highly relevant to the users' search.

Efficient Peer-to-Peer Lookup in Multi-hop Wireless Networks

  • Shin, Min-Ho;Arbaugh, William A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제3권1호
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    • pp.5-25
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    • 2009
  • In recent years the popularity of multi-hop wireless networks has been growing. Its flexible topology and abundant routing path enables many types of applications. However, the lack of a centralized controller often makes it difficult to design a reliable service in multi-hop wireless networks. While packet routing has been the center of attention for decades, recent research focuses on data discovery such as file sharing in multi-hop wireless networks. Although there are many peer-to-peer lookup (P2P-lookup) schemes for wired networks, they have inherent limitations for multi-hop wireless networks. First, a wired P2P-lookup builds a search structure on the overlay network and disregards the underlying topology. Second, the performance guarantee often relies on specific topology models such as random graphs, which do not apply to multi-hop wireless networks. Past studies on wireless P2P-lookup either combined existing solutions with known routing algorithms or proposed tree-based routing, which is prone to traffic congestion. In this paper, we present two wireless P2P-lookup schemes that strictly build a topology-dependent structure. We first propose the Ring Interval Graph Search (RIGS) that constructs a DHT only through direct connections between the nodes. We then propose the ValleyWalk, a loosely-structured scheme that requires simple local hints for query routing. Packet-level simulations showed that RIGS can find the target with near-shortest search length and ValleyWalk can find the target with near-shortest search length when there is at least 5% object replication. We also provide an analytic bound on the search length of ValleyWalk.

Hyperparameter Search for Facies Classification with Bayesian Optimization (베이지안 최적화를 이용한 암상 분류 모델의 하이퍼 파라미터 탐색)

  • Choi, Yonguk;Yoon, Daeung;Choi, Junhwan;Byun, Joongmoo
    • Geophysics and Geophysical Exploration
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    • 제23권3호
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    • pp.157-167
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    • 2020
  • With the recent advancement of computer hardware and the contribution of open source libraries to facilitate access to artificial intelligence technology, the use of machine learning (ML) and deep learning (DL) technologies in various fields of exploration geophysics has increased. In addition, ML researchers have developed complex algorithms to improve the inference accuracy of various tasks such as image, video, voice, and natural language processing, and now they are expanding their interests into the field of automatic machine learning (AutoML). AutoML can be divided into three areas: feature engineering, architecture search, and hyperparameter search. Among them, this paper focuses on hyperparamter search with Bayesian optimization, and applies it to the problem of facies classification using seismic data and well logs. The effectiveness of the Bayesian optimization technique has been demonstrated using Vincent field data by comparing with the results of the random search technique.