A Cross-Layer Route Discovery Framework for Mobile Ad Hoc Networks

A Cross-Layer Route Discovery Framework for Mobile Ad Hoc Networks

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Most reactive routing protocols in MANETs employ a random delay between rebroadcasting route requests (RREQ) in order to avoid "broadcast storms." However this can lead to problems such as "next hop racing" and "rebroadcast redundancy." In addition to this, existing routing protocols for MANETs usually take a single routing strategy for all flows.

This may lead to inefficient use of resources.In this paper we propose a Improvement the estimation of reference evapotranspiration by combining different types of meteorological data Using machine learning models cross-layer route discovery framework (CRDF) to address these problems by exploiting the cross-layer information.CRDF solves the above problems efficiently and enables a new technique: routing strategy automation (RoSAuto).

RoSAuto refers to the technique that each source node Popular Music, National Culture and the First Chervona Ruta Festival of 1989 automatically decides the routing strategy based on the application requirements and each intermediate node further adapts the routing strategy so that the network resource usage can be optimized.To demonstrate the effectiveness and the efficiency of CRDF, we design and evaluate a macrobian route discovery strategy under CRDF.