<XML><RECORDS><RECORD><REFERENCE_TYPE>10</REFERENCE_TYPE><REFNUM>8515</REFNUM><AUTHORS><AUTHOR>Bani Yassein,M.</AUTHOR><AUTHOR>Al-Humoud,S.</AUTHOR><AUTHOR>Ould Khaoua,M.</AUTHOR><AUTHOR>Mackenzie,L.M.</AUTHOR></AUTHORS><YEAR>2007</YEAR><TITLE>A Dynamic Counter Based Broadcast using Local Neighborhood Information in MANETs</TITLE><PLACE_PUBLISHED>DCS Technical Report Series</PLACE_PUBLISHED><PUBLISHER>Dept of Computing Science, University of Glasgow</PUBLISHER><ISBN>TR-2007-245</ISBN><LABEL>Bani Yassein:2007:8515</LABEL><KEYWORDS><KEYWORD>MANET</KEYWORD></KEYWORDS<ABSTRACT>Broadcasting in MANETs is a fundamental data dissemination mechanism, with important applications, e.g., heavily used in the route query process in many routing protocols, addresses resolution and diffusing information to the whole network (alarm signal for example). Broadcasting in MANETs has traditionally been based on flooding, which overwhelm the network with large number of rebroadcast packets in order to reach all network nodes. However, flooding induces what is known as the “broadcast storm problem” which causes severe degradation in network performance due to excessive redundant retransmission, collision and contention. Counter based flooding has been one of the earliest suggested approaches to broadcasting. Counter based threshold value of such nodes should be set lower than nodes situated in denser regions. In order to fix the counter based threshold value, we have analysed extensively the topological characteristics of a MANET when nodes move according to the widely adopted random way point mobility model. The higher is the number of neighbours, the denser is the network region is. Similarly, the lower is the number of neighbours the sparser the network region is. Extensive simulation experiments have been performed in order to determine the minimum and maximum number of neighbours for a given node in the network for a wide range of scenarios. This research argues that such information could be used to better estimate the counter based threshold values at given node. To demonstrate that, this paper proposes new counter based algorithm that dynamically adjust the counter based threshold value as per the node distribution and node movement using one hop neighbourhood information. This is done based on locally available information and without requiring any assistance of distance measurements or exact location determination devices</ABSTRACT></RECORD></RECORDS></XML>