Applying the time-to-live parameter in on demand route caching in MANETs

  • Authors:
  • Spanakis Emmanouil;Apostolos Traganitis

  • Affiliations:
  • Department of Computer Science, Institute of Computer Science, FORTH, University of Crete, Heraklion, Crete, Greece;Department of Computer Science, Institute of Computer Science, FORTH, University of Crete, Heraklion, Crete, Greece

  • Venue:
  • ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 1
  • Year:
  • 2009

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Abstract

Low resource availability in Mobile Ad hoc NETworks (MANETs) requires efficient utilization of resources and imposes severe demands on routing protocols, motivating their study, since the existing (for wired networks) routing protocols perform poorly, due to the unique characteristics of MANETs. The Dynamic Source Routing (DSR) protocol is one of the most important, simple, and efficient reactive source routing protocols designed specifically for use in multi-hop mobile ad-hoc wireless networks. Source nodes use route caches to maintain previously discovered routes, leading to significantly smaller routing latency for later route requests, and to the reduction of the control traffic required for route discovery. However, prolonged storage of route caches may render them obsolete and when an invalid route is used, extra traffic overhead and routing delay is incurred to discover the broken links. In this work we assume a mobile ad hoc network that uses DSR to route packets. We study the management of routing data stored in the nodes' route caches by optimizing the cached route lifetime using a Time-To-Live (TTL) interval. The idea is to purge cache entries after some Time-To-Live (TTL) interval. Firstly we study the route lifetime for different route lengths in an ad-hoc wireless network. Secondly we compare our result with those obtained from a mathematical analysis and conclude that the use of this technique enables the protocol to avoid using routes that lead to routing errors and especially to time consuming errors. Finally we develop an algorithm that estimates the lifetime of aU routes in the network, and optimizes TTL settings in real time for every new discovered cached route, using OPNET modeler as the simulation environment.