DocumentCode :
2347852
Title :
Refined Cluster Based Mobility Prediction with Weighted Algorithm
Author :
Saini, Naveen Kumar ; Trivedi, Aditya
Author_Institution :
Dept. of Inf. Technol., ABV-IIITM, Gwalior, India
fYear :
2010
fDate :
26-28 Nov. 2010
Firstpage :
350
Lastpage :
354
Abstract :
Mobile Ad hoc networks (MANETs) are self organizing and self-configuring multi-hop wireless networks. They are able to re-configure themselves when they are affected by node mobility. In the field communication nodes are very sensitive to node mobility and it can be interrupted if the topology changes. If the mobility prediction is used to predict the future position of a node, the resources reservation can be made before the topology changes. In this paper, we proposed the use of a clustering based approach to predict the future position of mobile node in a neighboring cluster. We use a weighted algorithm to find Cluster head and gateways. In addition, we use the hello messages which are responsible for checking the routes so that route compatibility can be obtained. Mobility prediction affects the two aspects like application -oriented and service oriented in adhoc networks. Simulation experiments are conducted to measure the cluster head and gateways by using algorithm. Result shows that hello messages are adequate to predict the route for future location of high mobile nodes.
Keywords :
mobile ad hoc networks; mobility management (mobile radio); telecommunication network routing; MANET; hello message; mobile ad hoc networks; mobile node position; refined cluster based mobility prediction; route checking; route compatibility; self configuring multihop wireless network; self organizing multihop wireless network; weighted algorithm; MANET; mobility prediction; signal strength; weighted algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2010 International Conference on
Conference_Location :
Bhopal
Print_ISBN :
978-1-4244-8653-3
Electronic_ISBN :
978-0-7695-4254-6
Type :
conf
DOI :
10.1109/CICN.2010.78
Filename :
5701992
Link To Document :
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