Title :
Intelligent Multi-Path Selection Based on Parameters Prediction
Author :
Ju, Suyang ; Evans, Joseph B.
Author_Institution :
Univ. of Kansas Lawrence, Lawrence, KS
Abstract :
This paper provides a method for multi-path selection based on parameters prediction. In wireless networks, links with different bandwidths induce different end-to-end delay and the packet loss rate characteristics. It means that we should be able to gain some knowledge of the type of links given the end-to-end delay and the packet loss rate. In this work, we use a neural network machine learning method to infer the types of the links. After predicting the types of the links, we can choose the path based on the prediction of the incremental throughput, for example by choosing the path with the largest potential incremental throughput.
Keywords :
ad hoc networks; learning (artificial intelligence); mobile radio; neural nets; prediction theory; radio links; telecommunication computing; telecommunication network routing; end-to-end delay; incremental throughput; intelligent multipath selection; mobile ad hoc network; neural network machine learning method; packet loss rate characteristics; parameters prediction; wireless links; wireless networks; Bandwidth; Bit error rate; Communications Society; Delay; Energy measurement; Loss measurement; Mobile ad hoc networks; Neural networks; Routing protocols; Throughput;
Conference_Titel :
Communications Workshops, 2008. ICC Workshops '08. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2052-0
Electronic_ISBN :
978-1-4244-2052-0
DOI :
10.1109/ICCW.2008.106