Updating the Routing Position in Adhoc Networks by using Adaptive Position
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : Ravi Kumar Poluru , T. Sunil Kumar Reddy , D.Nagaraju|
|DOI : 10.14445/22312803/IJCTT-V10P127|
Ravi Kumar Poluru , T. Sunil Kumar Reddy , D.Nagaraju."Updating the Routing Position in Adhoc Networks by using Adaptive Position". International Journal of Computer Trends and Technology (IJCTT) V10(3):160-166, Apr 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
In geographic routing, nodes to theirinstantaneous neighbors call for to maintain up-to-date positions for making successfulforwarding decisions. The geographic location coordinates of the nodes by the periodic broadcasting of beacon packetsis atrendy method used by the majority geographic routing protocols to preserve neighbor positions. We contend and display that periodicbeaconing apart from of the node mobility and traffic patterns in the network is not nice-looking from both update cost and routingrecital points of view. We recommend the Adaptive Position Update (APU) strategy for geographic routing, which enthusiasticallyadjusts the occurrence of position updates based on the mobility dynamics of the nodes and the forwarding patterns in the system. APUis based on two easy principles: 1) nodes whose arrangements are harder to guess update their positions more recurrently (and viceversa), and (ii) nodes faster to forwarding paths update their positions more recurrently (and vice versa). Our speculative analysis, whichis validated by NS2 simulations of a well-known geographic routing procedure, Greedy Perimeter Stateless Routing Protocol (GPSR),shows that APU can drastically reduce the update cost and pick up the routing performance in terms of packet delivery ratio andregular end-to-end delay in assessment with periodic beaconing and other recently proposed updating schemes. The benefits of APUare additional confirmed by responsibility evaluations in realistic network scenarios, which account for localization error, practical radiopropagation, and sparse system.
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Wireless Communication, protocol analysis, routing algorithms, Mobility Prediction, on-demand Rule.