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Load balancing algorithms based on gradient methods and their analysis through algebraic graph theory

机译:基于梯度法的负载均衡算法及其代数图理论分析

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The main results of this paper are based on the idea that most load balancing algorithms can be described in the framework of optimization theory. It enables to involve classical results linked with convergence, its speed and other elements. We emphasize that these classical results have been found independently and till now this connection has not been shown clearly. In this paper, we analyze the load balancing algorithm based on the steepest descent algorithm. The analysis shows that the speed of convergence is determined by eigenvalues of the Laplacian for the graph of a given load balancing system. This consideration also leads to the problems of choosing an optimal structure for a load balancing system. We prove that these optimal graphs have special Laplacians: the multiplicities of their minimal and maximal positive eigenvalues must be greater than one. Such a property is essential for strongly regular graphs, investigated in algebraic graph theory.
机译:本文的主要结果是基于这样的思想,即大多数负载平衡算法都可以在优化理论的框架内进行描述。它可以涉及与收敛,速度和其他要素相关的经典结果。我们强调,这些经典结果是独立发现的,到目前为止,这种联系还没有清楚地显示出来。在本文中,我们分析了基于最速下降算法的负载均衡算法。分析表明,对于给定的负载平衡系统,图的收敛速度取决于拉普拉斯算子的特征值。这种考虑还导致了为负载平衡系统选择最佳结构的问题。我们证明了这些最优图具有特殊的拉普拉斯算子:它们的最小和最大正特征值的多重性必须大于1。对于代数图论研究的强正则图来说,这种特性是必不可少的。

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