<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>9016</REFNUM><AUTHORS><AUTHOR>Bani Yassein,M.</AUTHOR><AUTHOR>Ould-Khaoua,M.</AUTHOR><AUTHOR>Mackenzie,L.M.</AUTHOR><AUTHOR>Papanastasiou,S.</AUTHOR><AUTHOR>Jamal-deen,A.</AUTHOR></AUTHORS><YEAR>2006</YEAR><TITLE>Improving route discovery in on-demand routing protocols using local topology information in MANETs</TITLE><PLACE_PUBLISHED>International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive Proceedings of the ACM international workshop on Performance monitoring, measurement, and evaluation of heterogeneous wireless and wired networks</PLACE_PUBLISHED><PUBLISHER>ACM</PUBLISHER><PAGES>95-99</PAGES><ISBN>1-59593-502-9</ISBN><LABEL>Bani Yassein:2006:9016</LABEL><ABSTRACT>Most existing routing protocols proposed for MANETs use flooding as a broadcast technique for the propagation of network control packets; a particular example of this is the dissemination of route requests (RREQs), which facilitate route discovery. In flooding, each mobile node rebroadcasts received packets, which, in this manner, are propagated network-wide with considerable overhead. This paper improves on the performance of existing routing protocols by reducing the communication overhead incurred during the route discovery process by implementing a new broadcast algorithm called the adjusted probabilistic flooding on the Ad-Hoc on Demand Distance Vector (AODV) protocol. AODV [3] is a well-known and widely studied algorithm which has been shown over the past few years to maintain an overall lower routing overhead compared to traditional proactive schemes, even though it uses flooding to propagate RREQs. Our results, as presented in this paper, reveal that equipping AODV with fixed and adjusted probabilistic flooding, instead, helps reduce the overhead of the route discovery process whilst maintaining comparable performance levels in terms of saved rebroadcasts and reachability as achieved by conventional AODV. Moreover, the results indicate that the adjusted probabilistic technique results in better performance compared to the fixed one for both of these metrics</ABSTRACT></RECORD></RECORDS></XML>