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Neural network techniques for scheduling and routing problems in multihop radio networks

机译:用于多跳无线电网络中的调度和路由问题的神经网络技术

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The authors address the problem of link activation or scheduling in multihop packet radio networks, a contention-free form of channel access that is appropriate for many military communication applications. This problem, in almost all of its forms, is a combinatorial-optimization problem of high complexity. They approach this problem by the use of a Hopfield neural network model in which the method of Lagrange multipliers is used to dynamically vary the values of the coefficients used in the connection weights. Extensive software simulation results demonstrate the effectiveness of this approach in producing schedules of optimal length. Issues associated with the extension of this approach to the joint routing/scheduling problem are discussed.
机译:作者解决了多跳分组无线网络中链路激活或调度的问题,这是一种适用于许多军事通信应用的无争用形式的信道访问。几乎所有形式的该问题都是高复杂度的组合优化问题。他们通过使用Hopfield神经网络模型解决了这个问题,在该模型中,拉格朗日乘数法用于动态改变连接权重中使用的系数值。大量的软件仿真结果证明了这种方法在生成最佳长度的计划中的有效性。讨论了与将这种方法扩展到联合路由/调度问题相关的问题。

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