Path Selection in Mobile Ad-Hoc Networks and Distribution of Path Duration

We investigate the issue of path selection in mobile multi-hop wireless networks. We are interested in designing a path selection algorithm that maximizes the expected duration of the selected path. To this end we first study the distribution of path duration. We show that, under a set of mild conditions, when the hop count along a path is large, the distribution of path duration can be well approximated by an exponential distribution even when link durations are dependent and their distributions are heterogeneous. Second, we investigate the relation between a path duration and durations of the links along the path. We prove that the parameter of the exponential distribution, which determines the expected duration of the path, is related to the link durations only through their means and is given by the sum of the inverses of the expected link durations. We validate our analytical results using ns-2 simulation with the Random Waypoint and Manhattan mobility models.

[1]  Chai-Keong Toh,et al.  Ad Hoc Mobile Wireless Networks , 2002 .

[2]  David Tse,et al.  Mobility increases the capacity of ad hoc wireless networks , 2002, TNET.

[3]  Teresa H. Meng,et al.  Minimum energy mobile wireless networks , 1998, ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220).

[4]  Charles E. Perkins,et al.  Ad-hoc on-demand distance vector routing , 1999, Proceedings WMCSA'99. Second IEEE Workshop on Mobile Computing Systems and Applications.

[5]  Charles E. Perkins,et al.  Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers , 1994, SIGCOMM.

[6]  Malcolm R Leadbetter,et al.  On extreme values in stationary sequences , 1974 .

[7]  Ahmed Helmy,et al.  PATHS: analysis of PATH duration statistics and their impact on reactive MANET routing protocols , 2003, MobiHoc '03.

[8]  Distribution of path durations in mobile ad-hoc networks - Palm's Theorem to the rescue , 2006, Comput. Networks.

[9]  J. Broch,et al.  Dynamic source routing in ad hoc wireless networks , 1998 .

[10]  Malcolm R Leadbetter,et al.  Extremes and local dependence in stationary sequences , 1983 .

[11]  Subramanian Ramanathan,et al.  Scheduling algorithms for multi-hop radio networks , 1992, SIGCOMM '92.

[12]  G. S. Watson,et al.  Extreme Values in Samples from $m$-Dependent Stationary Stochastic Processes , 1954 .

[13]  Leandros Tassiulas,et al.  Energy conserving routing in wireless ad-hoc networks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[14]  Ivan Stojmenovic,et al.  Ad hoc Networking , 2004 .

[15]  David A. Maltz,et al.  Dynamic Source Routing in Ad Hoc Wireless Networks , 1994, Mobidata.

[16]  Roy D. Yates,et al.  Probability and stochastic processes , 1998 .

[17]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[18]  M. S. Corson,et al.  A highly adaptive distributed routing algorithm for mobile wireless networks , 1997, Proceedings of INFOCOM '97.

[19]  Christian Wagner,et al.  The Spatial Node Distribution of the Random Waypoint Mobility Model , 2002, WMAN.

[20]  Subramanian Ramanathan,et al.  Scheduling algorithms for multihop radio networks , 1993, TNET.

[21]  Jean-Yves Le Boudec Understanding the simulation of mobility models with Palm calculus , 2007, Perform. Evaluation.

[22]  Daniel P. Heyman,et al.  Stochastic models in operations research , 1982 .