Trajectory Estimation for Wireless Mobile Networks Using Polynomial Regression

Abstract

Trajectory Estimation for Wireless Mobile Networks Using Polynomial RegressionArbitrary and random motion of mobile ad hoc network nodes while communicating results in frequent topology changes and multiple disconnections of links. This dynamic environment challenges the routing of data from the source to the destination and imposes the need for prediction models to track these changes, and then determine future topology of the network. The prediction of network mobility into the future will reduce the frequency of location updates for geographical routing protocols. Moreover it will reduce route request delay and the frequency of route updates in topology based protocols. This paper proposes a predictive model called polynomial regression trajectory estimation. This model is based on the regular behavior of nodes and uses polynomial regression to allow each mobile node to estimate its future locations as a function of time. The estimated locations will be disseminated to the network so that nodes can use them to estimate the future topologies of the entire network. The efficiency of the proposed model has been evaluated by MATLAB simulation.