• Title/Summary/Keyword: Adaptive Partition

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Adaptive Partitioning for Efficient Query Support

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.5 no.4
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    • pp.369-373
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    • 2007
  • RFID systems large volume of data, it can lead to slower queries. To achieve better query performance, we can partition into active and some nonactive data. In this paper, we propose two approaches of partitioning for efficient query support. The one is average period plus delta partition and the other is adaptive average period partition. We also present the system architecture to manage active data and non-active data and logical database schema. The data manager check the active partition and move all objects from the active store to an archive store associated with an average period plus data and an adaptive average period. Our experiments show the performance of our partitioning methods.

Adaptive Partition-Based Address Allocation Protocol in Mobile Ad Hoc Networks

  • Kim, Ki-Il;Peng, Bai;Kim, Kyong-Hoon
    • Journal of information and communication convergence engineering
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    • v.7 no.2
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    • pp.141-147
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    • 2009
  • To initialize and maintain self-organizing networks such as mobile ad hoc networks, address allocation protocol is essentially required. However, centralized approaches that pervasively used in traditional networks are not recommended in this kind of networks since they cannot handle with mobility efficiently. In addition, previous distributed approaches suffer from inefficiency with control overhead caused by duplicated address detection and management of available address pool. In this paper, we propose a new dynamic address allocation scheme, which is based on adaptive partition. An available address is managed in distributed way by multiple agents and partitioned adaptively according to current network environments. Finally, simulation results reveal that a proposed scheme is superior to previous approach in term of address acquisition delay under diverse simulation scenarios.

A Diagnosis Algorithm for Hypercube Multiprocessors using Adaptive Cube Partition Method (적응적 큐브 분할을 이용한 하이퍼큐브 진단 알고리즘)

  • Choi, Moon-Ok;Rhee, Chung-Sei
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.4
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    • pp.431-439
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    • 2000
  • In this paper, we propose a system-level diagnosis algorithm for hypercube muti-processors using adaptive cube partition method. Feng[1] proposed a diagnosis algorithm for hypercube multiprocessors which gives a better performance compared to previous researches[2, 3]. But cube partitions in Feng's algorithm are performed without syndrome analysis. Therfore unnecessery overhead is made during cube partitions. In this paper, we propose an adaptive cube partition method which gives better partition through syndrome analysis and reduces diagnosis cost. We give a simulation result for comparisons. We have found that our algorithm shows better performance compared to Feng's method.

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Performance Analysis of Adaptive Partition Cache Replacement using Various Monitoring Ratios for Non-volatile Memory Systems

  • Hwang, Sang-Ho;Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.1-8
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    • 2018
  • In this paper, we propose an adaptive partition cache replacement policy and evaluate the performance of our scheme using various monitoring ratios to help lifetime extension of non-volatile main memory systems without performance degradation. The proposal combines conventional LRU (Least Recently Used) replacement policy and Early Eviction Zone (E2Z), which considers a dirty bit as well as LRU bits to select a candidate block. In particular, this paper shows the performance of non-volatile memory using various monitoring ratios and determines optimized monitoring ratio and partition size of E2Z for reducing the number of writebacks using cache hit counter logic and hit predictor. In the experiment evaluation, we showed that 1:128 combination provided the best results of writebacks and runtime, in terms of performance and complexity trade-off relation, and our proposal yielded up to 42% reduction of writebacks, compared with others.

Partition and Caching Mechanism for GML Visualization on Mobile Device (모바일 디바이스에서 GML 가시화를 위한 분할 및 캐싱 기법)

  • Song, Eun-Ha;Park, Yong-Jin;Han, Won-Hee;Jeong, Young-Sik
    • Journal of Korea Multimedia Society
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    • v.11 no.7
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    • pp.1025-1034
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    • 2008
  • In this paper, we developed GridGML for efficiently supplying a GML and visualizing the map with partitioning map and caching method to a mobile device. In order to overcome the weighting of a file, which is the biggest weakness of a GML, GridGML extracts only the most necessary parts for the visualization of the map among GML attributes, and makes the file light as a class instance by applying an offset value. GridGML manages a partition based on the visualization area of a mobile device to visualize the map to a mobile device in real time, and transmits the partition area by serializing it for the benefit of transmission. Also, the received partition area is compounded in a mobile device and is visualized by being partitioned again as four visible areas based on the display of a mobile device. Then, the area is managed by applying a caching algorithm in consideration of repetitiveness for a received map for the efficient operation of resources. Also, in order to prevent the delay in transmission time as regards the instance density area of the map, an adaptive map partition mechanism is proposed for maintaining the transmission time uniformly.

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Input Variable Selection by Using Fixed-Point ICA and Adaptive Partition Mutual Information Estimation (고정점 알고리즘의 독립성분분석과 적응분할의 상호정보 추정에 의한 입력변수선택)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.525-530
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    • 2006
  • This paper presents an efficient input variable selection method using both fixed-point independent component analysis(FP-ICA) and adaptive partition mutual information(AP-MI) estimation. FP-ICA which is based on secant method, is applied to quickly find the independence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function(PDF). The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the FP-ICA and regular partition MI estimation.

Wavelet based Embedded Video Coding with 3-D Block Partition (3-D 블록분할을 이용하는 웨이브렛 기반 임베디드 비디오 부호화)

  • 양창모;임태범;이석필
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.133-136
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    • 2003
  • In this paper, we propose a low bit-rate embedded video coding scheme with 3-D block partition in the wavelet domain. The proposed video coding scheme includes multi-level three dimensional dyadic wavelet decomposition, raster scanning within each subband, partitioning of blocks, and adaptive arithmetic entropy coding. Although the proposed video coding scheme is quite simple, it produces bit-streams with good features, including SNR scalability from the embedded nature. Experimental results demonstrate that the proposed video coding scheme is quite competitive to other good wavelet-based video coders in the literature.

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A Memory-based Reasoning Algorithm using Adaptive Recursive Partition Averaging Method (적응형 재귀 분할 평균법을 이용한 메모리기반 추론 알고리즘)

  • 이형일;최학윤
    • Journal of KIISE:Software and Applications
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    • v.31 no.4
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    • pp.478-487
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    • 2004
  • We had proposed the RPA(Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked not bad in many area, however, the major drawbacks of RPA are it's partitioning condition and the way of extracting major patterns. We propose an adaptive RPA algorithm which uses the FPD(feature-based population densimeter) to stop the ARPA partitioning process and produce, instead of RPA's averaged major pattern, optimizing resulting hyperrectangles. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed an excellent results in terms of classification when we compare it to the k-NN.

Input Variables Selection by Principal Component Analysis and Mutual Information Estimation (주요성분분석과 상호정보 추정에 의한 입력변수선택)

  • Cho, Yong-Hyun;Hong, Seong-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.220-225
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    • 2007
  • This paper presents an efficient input variable selection method using both principal component analysis(PCA) and adaptive partition mutual information(AP-MI) estimation. PCA which is based on 2nd order statistics, is applied to prevent a overestimation by quickly removing the dependence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function. The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively. The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the PCA and regular partition MI estimation.

Embedded Video Compression Scheme using Wavelet Transform and 3-D Block Partition (Wavelet 변환과 3-D 블록분할을 이용하는 Embedded 비디오 부호화기)

  • Yang, Change-Mo;Lim, Tae-Beom;Lee, Seok-Pil
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.190-192
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    • 2004
  • In this paper, we propose a low bit-rate embedded video compression scheme with 3-D block partition coding in the wavelet domain. The proposed video compression scheme includes multi-level 3-dimensional dyadic wavelet decomposition, raster scanning within each subband, formation of block, 3-D partitioning of block, and adaptive arithmetic entropy coding. Although the proposed video compression scheme is quit simple, it produces bit-stream with good features, including SNR scalability from the embedded nature. Experimental results demonstrate that the proposed video compression scheme is quit competitive to other good wavelet-based video coders in the literature.

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