LAUSR

Mobile ad hoc networks (MANETs) are wireless networks that include many peer nodes. The node mobility in the MANETs leads to several issues like maintenance of paths, lifespan of the battery, safety, reliability and unpredictable link traits. All these in turn would adversely affect the network Quality of Service (QoS). In MANETs, a major role is played by the routing protocol for discovering as well as maintaining the paths. There are two types of routing: uni-path and multi-path. The MANET network can be made more reliable using the multipath routing protocol. The focus of this research is evaluating the multipath routing protocol for QoS. For better delivering of data, the Ad hoc On-demand Multipath Distance Vector (AOMDV) has improved methods. This maintains the QoS in terms of factors like MANET end-to-end delay, hop count and bandwidth. This work explores the evolutionary computation schemes for optimizing the routing. The discovery of QoS route in multi-constrained network is a complex problem, this is solved optimally using heuristic algorithms. In that, specifically used for intrusion detection programs in such challenging set ups would be Grammatical Evolution (GE). For finding out familiar threats in MANETs, the natural evolution-motivated GE scheme has been applied. The outcomes have shown that in MANETs, the proposed AOMDV-QoS schemes fulfill the Quality of Service requirements along with lesser delay and high reliability.