首页> 外文会议> >Autoregressive, moving average and mixed autoregressive-moving average processes for forecasting QoS in ad hoc networks for real-time service support
【24h】

Autoregressive, moving average and mixed autoregressive-moving average processes for forecasting QoS in ad hoc networks for real-time service support

机译:自回归,移动平均和混合自回归-移动平均过程,用于预测ad hoc网络中的QoS,以提供实时服务支持

获取原文

摘要

We try to reduce the degree of degradation of QoS and at the same time ameliorate the estimation of the QoS of wireless ad-hoc networks. In fact, we present methods for forecasting resources to meet the QoS requirements in ad-hoc networks based on autoregressive (AR), moving average (MA) and mixed autoregressive-moving average (ARMA) processes. The results obtained show that the combination of the ad hoc routing protocol DSR with forecasting QoS mechanisms for real-time service support, based on AR, MA and ARMA processes, performs better.
机译:我们尝试减少QoS的降低程度,同时改善无线自组网QoS的估计。实际上,我们基于自回归(AR),移动平均(MA)和混合自回归移动平均(ARMA)流程,提出了用于预测满足ad-hoc网络中QoS要求的资源的方法。获得的结果表明,基于AR,MA和ARMA流程,ad hoc路由协议DSR与用于实时服务支持的预测QoS机制相结合,效果更好。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号