Testing of random matrices

Let $n$ be a positive integer and $X = [x_{ij}]_{1 \leq i, j \leq n}$ be an $n \times n$\linebreak \noindent sized matrix of independent random variables having joint uniform distribution \hbox{Pr} {x_{ij} = k \hbox{for} 1 \leq k \leq n} = \frac{1}{n} \quad (1 \leq i, j \leq n) \koz. A realization $\mathcal{M} = [m_{ij}]$ of $X$ is called \textit{good}, if its each row and each column contains a permutation of the numbers $1, 2,..., n$. We present and analyse four typical algorithms which decide whether a given realization is good

Load Redistribution on Hypercubes in the Presence of Faults

In this paper, we present load redistribution algorithms for hypercubes in the presence of faults. Our algorithms complete in low-order polynomial of the number of faulty nodes and exhibit excellent experimental performance. These algorithms are topology independent and can be applied to a wide variety of networks