Resource prediction based routing using wavelet neural network in mobile ad-hoc networks

Many multimedia applications over Mobile Ad hoc NETworks (MANETs) require Quality of Service (QoS) to meet real-time services. Routing, an important component for QoS provisioning, affected by many factors such as limited resources, shared channel, unpredictable mobility, improper load balancing, and variation in signal strength. QoS based routing protocol must consider efficient usage of resources. In this paper, we propose a resource prediction based routing in MANET that routes the packets based on future availability of buffer-space, energy and bandwidth resources. Future availability of these resources is predicted using wavelet neural networks based traffic and mobility prediction model. The proposed routing scheme is simulated to evaluate the performance in terms of packet delivery ratio, computation overhead, memory overhead and packet delay.

[1]  Lajos Hanzo,et al.  Quality of Service Routing and Admission Control for Mobile Ad-hoc Networks with a Contention-based MAC Layer , 2006, 2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems.

[2]  Farouk Kamoun,et al.  Microsoft Word-V1-I1-P95-101 , 2010 .

[3]  Xu Lan.  Analysis and research of several network traffic prediction models , 2013, 2013 Chinese Automation Congress.

[4]  Rajashekhar C. Biradar,et al.  Resource prediction using wavelet neural network in mobile ad-hoc networks , 2014, 2014 International Conference on Advances in Electronics Computers and Communications.

[5]  Klara Nahrstedt,et al.  Optimal resource allocation in wireless ad hoc networks: a price-based approach , 2006, IEEE Transactions on Mobile Computing.

[6]  Yantai Shu,et al.  Study on network traffic prediction techniques , 2005, Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005..

[7]  Sunilkumar S. Manvi,et al.  Neighbor supported reliable multipath multicast routing in MANETs , 2012, Journal of Network and Computer Applications.

[8]  Jian-Chang Lu,et al.  Research on the Application of the Wavelet Neural Network Model in Peak Load Forecasting Considering of the Climate Factors , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[9]  Xing-an Fu,et al.  A network traffic prediction model based on recurrent wavelet neural network , 2012, Proceedings of 2012 2nd International Conference on Computer Science and Network Technology.

[10]  Jun Xu,et al.  Multiplicity adjustment for intersection-union test: detecting overlapping genes from multiple microarray gene lists , 2007 .

[11]  N. Pindoriya,et al.  An Adaptive Wavelet Neural Network-Based Energy Price Forecasting in Electricity Markets , 2008, IEEE Transactions on Power Systems.