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arXiv 0807.1158cs.ITmath.IT
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标量线性网络编码问题的路径增益代数表示

Path Gain Algebraic Formulation for the Scalar Linear Network Coding Problem

Abhay T. Subramanian, Andrew Thangaraj

摘要:

在代数观点中,网络编码问题的解决方案被视为由多项式方程组指定的变量,该多项式方程组通常通过使用边到边增益作为变量导出。每个汇的输出等于其需求,以获得多项式方程。在这项工作中,我们提出了一种方法来推导多项式方程使用源到宿路径增益作为变量。在路径增益公式中,我们证明了线性和二次方程就足够了;因此,网络编码等价于一个最大次数为2的多项式方程系统。我们提出的算法生成的路径增益和路径增益的解决方案,边缘到边缘的增益解决方案的方程。由于阶数低,所以对于使用路径增益获得的方程组来说,简化是容易的。使用小规模的网络编码问题,我们表明,路径增益的方法在更简单的方程,并确定在某些情况下的问题的可解性。在一个更大的网络(有87个节点和161条边)上,我们展示了路径增益方法如何继续为一些网络编码问题提供确定性解决方案。

英文摘要:

In the algebraic view, the solution to a network coding problem is seen as a variety specified by a system of polynomial equations typically derived by using edge-to-edge gains as variables. The output from each sink is equated to its demand to obtain polynomial equations. In this work, we propose a method to derive the polynomial equations using source-to-sink path gains as the variables. In the path gain formulation, we show that linear and quadratic equations suffice; therefore, network coding becomes equivalent to a system of polynomial equations of maximum degree 2. We present algorithms for generating the equations in the path gains and for converting path gain solutions to edge-to-edge gain solutions. Because of the low degree, simplification is readily possible for the system of equations obtained using path gains. Using small-sized network coding problems, we show that the path gain approach results in simpler equations and determines solvability of the problem in certain cases. On a larger network (with 87 nodes and 161 edges), we show how the path gain approach continues to provide deterministic solutions to some network coding problems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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