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From link dynamics to path lifetime and packet-length optimization in MANETs

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Abstract

We present an analytical framework and statistical models to accurately characterize the lifetime of a wireless link and multi-hop paths in mobile ad hoc networks (MANET). We show that the lifetimes of links and paths can be computed through a two-state Markov model. We also show that the analytical solution follows closely the results obtained through discrete-event simulations for two mobility models, namely, random direction and random waypoint mobility models. We apply these models to study practical implications of link lifetime on routing protocols. First, we compute optimal packet lengths as a function of mobility, and show that significant throughput improvements can be attained by adapting packet lengths to the mobility of nodes in a MANET. Second, we show how the caching strategy of on-demand routing protocols can benefit from considering the link lifetimes in a MANET. Finally,we summarize all the analytical results into a comprehensive performance analysis on throughput, delay and storage.

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Notes

  1. In mobile ad hoc network, the traffic is generated randomly and nodes are moving randomly. When a node initiate traffic to other nodes, the target node could be anywhere in the network and the realys could also be anywhere in the communication range. Therefore, a uniform distribution assumption naturally fits into the scenario.

  2. We recall that \(f(n)=\Uptheta(g(n)\) means there exist positive constants c 1,c 2 and M, such that \(0 \leq c_1 g(n) \leq f(n) \leq c_2 g(n)\forall n > M\).

  3. Equivalently, we can transfer K to the other side of this equation. It means that when the number of hops increases for a constant bandwidth B, the packet length should decrease.

  4. For delay to be finite, the arrival rate must be strictly less than the service rate but in this case, symmetric movements lead to a fully loaded tandem queue. To avoid this, we assume that if the available throughput is \(\Uplambda (n),\) each source generates traffic at a rate \((1-\epsilon)\Uplambda (n)\), for some ε > 0.

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Acknowledgements

The authors would like to thank Dr. Robin Groenevelt and Prof. Philippe Nain of INRIA Institute for their kind help on providing the simulation environment.

This work was supported in part by the US Army Research Office under grants W911NF-04-1-0224, W911NF-05-1-0246 and by the Baskin Chair of Computer Engineering. Opinion, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by the Department of Defense.

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Authors and Affiliations

  1. University of California at Santa Cruz, Santa Cruz, CA, 95064, USA

    Xianren Wu, Hamid R. Sadjadpour & J. J. Garcia-Luna-Aceves

  2. Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA, 94304, USA

    J. J. Garcia-Luna-Aceves

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  1. Xianren Wu
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  2. Hamid R. Sadjadpour
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  3. J. J. Garcia-Luna-Aceves
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Correspondence to Xianren Wu.

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Wu, X., Sadjadpour, H.R. & Garcia-Luna-Aceves, J.J. From link dynamics to path lifetime and packet-length optimization in MANETs. Wireless Netw 15, 637–650 (2009). https://doi.org/10.1007/s11276-007-0086-x

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