Call for Papers 2024

Feb 2024 - Volume 15, Issue 1
Deadline: 15 Jan 2024
Publication: 20 Feb 2024

Apr 2024 - Volume 15, Issue 2
Deadline: 15 Mar 2024
Publication: 20 Apr 2024




Title : Recognition and Elimination of Malicious Nodes in Vehicular Ad hoc Networks (VANETís)
Authors : Prashant Sangulagi, Mallikarjun Sarsamba, Mallikarjun Talwar, Vijay Katgi
Keywords : VANET, Mobile Agents, Routing, Malicious Nodes, Mobility.
Issue Date : Feb-Mar 2013
Abstract :
A Vehicular Ad-Hoc Network, or VANET, is a form of Mobile ad-hoc network, to provide communications among nearby vehicles and between vehicles and nearby fixed equipment (Base Stations) via radio waves. These have similar characteristics as mobile ad hoc networks, often in the form of multi-hop networks. Due to the high mobility of nodes network topology changes occur frequently. All nodes share the same channel leading to congestion in very dense networks. One important property that characterizes VANETs is that they are self-organizing, self-creating, and self administering and decentralized systems. This paper proposes detection and elimination of misbehaving nodes in VANETs using mobile agents. Mobile agents are employed for each node, for the collection of information of neighbours and to find the route from source to the destination. To find the malicious nodes among the intermediate nodes, mobility and power ratio of the intermediate nodes are continuously monitored with the help of software agents. Some threshold value of mobility and power ratio for intermediate nodes are maintained at the source node. Based on comparing the monitored and threshold values of these factors, with probabilistic approach we are determining the nodes as malicious nodes. Once the intermediate node is determined as the malicious node, the alternate path is employed from source to the destination. To test the operative effectiveness and performance of the system some of the performance parameters evaluated are, Number of paths available, Number of routes involving misbehaving nodes, Number of misbehaving nodes, Time taken to detect misbehaving nodes.
Page(s) : 16-22
ISSN : 0976-5166
Source : Vol. 4, No.1