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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Linear network coding ： ウィキペディア英語版 Linear network coding Linear network coding is a technique which can be used to improve a network's throughput, efficiency and scalability, as well as resilience to attacks and eavesdropping. Instead of simply relaying the packets of information they receive, the nodes of a network take ''several'' packets and combine them together for transmission. This can be used to attain the maximum possible information flow in a network. It has been proven that linear coding is enough to achieve the upper bound in multicast problems with one or more sources.〔S. Li, R. Yeung, and N. Cai, "Linear Network Coding"((PDF )), in IEEE Transactions on Information Theory, Vol 49, No. 2, pp. 371–381, 2003〕 However linear coding is not sufficient in general (e.g. multisource, multisink with arbitrary demands), even for more general versions of linearity such as convolutional coding and filter-bank coding.〔R. Dougherty, C. Freiling, and K. Zeger, "Insufficiency of Linear Coding in Network Information Flow" ((PDF )), in IEEE Transactions on Information Theory, Vol. 51, No. 8, pp. 2745-2759, August 2005 ( (erratum ))〕 Finding optimal coding solutions for general network problems with arbitrary demands remains an open problem. == Encoding and decoding == In a linear network coding problem, a group of nodes $P$ are involved in moving the data from $S$ source nodes to $K$ sink nodes. Each node generates new packets which are linear combinations of earlier received packets, multiplying them by coefficients chosen from a finite field, typically of size $GF(2^s)$. Each node, $p\_k$ with indegree, $InDeg(p\_k)\; =\; S$, generates a message $X\_k$ from the linear combination of received messages $\backslash \_^S$ by the relation: :$X\_k\; =\; \backslash sum\_^S\; g\_k^i\backslash cdot\; M\_i$ where the values $g\_k^i$ are the coefficients selected from $GF(2^s)$. Note that, since operations are computed in a finite field, the generated message is of the same length as the original messages. Each node forwards the computed value $X\_k$ along with the coefficients, $g\_k^i$, used in the $k^\backslash text$ level, $g\_k^i$. Sink nodes receive these network coded messages, and collect them in a matrix. The original messages can be recovered by performing Gaussian elimination on the matrix.〔.〕 In reduced row echelon form, decoded packets correspond to the rows of the form $e\_i=(...\; 0\; 1\; 0\; ...\; 0)$. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Linear network coding」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.