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

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.