Neural Networks Approach for Congestion Avoidance in Mobile Ad hoc Networks
Kumari Shambhavi1, Rajnesh Singh2

1Kumari Shambhavi, Research Scholar, IEC College Greater Noida (Uttar Pradesh), India.
2Rajnesh Singh, Hod, Department of CSE, IEC College, IEC College Greater Noida (Uttar Pradesh), India.
Manuscript received on 17 June 2019 | Revised Manuscript received on 11 July 2019 | Manuscript Published on 17 July 2019 | PP: 826-830 | Volume-8 Issue-1C2 May 2019 | Retrieval Number: A11410581C219/2019©BEIESP
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Abstract: The mobile ad hoc network is the decentralized type of network in which mobile nodes can join or leave the network. Due to such type of network quality of service is the major issue of this network. In this research work, AODV routing protocol is modified for congestion avoidance in the network. In the modification neural networks are applied for the congestion avoidance. The proposed technique is implemented in NS2 and results are analyzed in terms of certain parameters. The proposed technique shows high performance than existing AODV protocol in terms of throughput and packetloss.
Keywords: AODV, Neural Networks, Back Propagation.
Scope of the Article: Mobile Adhoc Network