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Non stationary stochastic models for forecasting QoS in ad hoc networks for real-time service support

机译：非固定随机模型，用于预测ad hoc网络中的QoS，以提供实时服务支持

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In this paper, we try to reduce the degree of QoS degradation while enhancing at the same time the estimation of the quality of service of the networks. We shall present methods for forecasting resources to meet the QoS requirements for real-time service support based on autoregressive integrated moving average processes: ARIMA combined with the ad hoc routing protocol: DSR. These processes provide a range of models, stationary and non-stationary, that adequately represent many of the time QoS variations. The results obtained (in terms of throughputs and end-to-end delays) show that the combination of the DSR protocol with the time QoS forecasting, based on ARIMA processes, performs better than conventional DSR.
机译：在本文中，我们试图降低QoS下降的程度，同时增强对网络服务质量的估计。我们将基于自回归综合移动平均过程：ARIMA和自组织路由协议：DSR，提出用于满足实时服务支持的QoS要求的资源预测方法。这些过程提供了固定和非固定的一系列模型，这些模型足以代表许多时间QoS的变化。获得的结果（就吞吐量和端到端延迟而言）表明，基于ARIMA流程的DSR协议与时间QoS预测的组合比常规DSR表现更好。

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