Using localized random walks to model Delay-Tolerant Networks

Mobile wireless delay-tolerant networks (DTNs) are wireless networks that suffer from intermittent connectivity, but enjoy the benefit of mobile nodes that can store, carry, and forward packets or messages, bringing them closer to their destinations through a selective forwarding policy. The evaluation of DTN routing protocols has primarily relied on simulation because most theoretical mobility models are unable to represent the mobility patterns that such protocols seek to take advantage of. In this paper we present and analyze a mobility model that we call localized random walk. This model is simple enough that it can be incorporated into mathematical models, but is spatially localized, which unlike other common mobility models, will make it possible to showcase the properties of heuristic-based DTN routing protocols. We derive the stationary spatial distribution of the mobility model, approximate what we call its spatial cross section, approximate the properties of its interaction with nodes following other mobility models, and use it to model some relatively simple DTN scenarios.

[1]  J. Giujs CENTRALLY BIASED DISCRETE RANDOM WALK , 1956 .

[2]  Gunter Bolch,et al.  Queueing Networks and Markov Chains , 2005 .

[3]  Paolo Giaccone,et al.  Capacity scaling in delay tolerant networks with heterogeneous mobile nodes , 2007, MobiHoc '07.

[4]  Matthias Grossglauser,et al.  Island Hopping: Efficient Mobility-Assisted Forwarding in Partitioned Networks , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[5]  Amin Vahdat,et al.  Epidemic Routing for Partially-Connected Ad Hoc Networks , 2009 .

[6]  David Kotz,et al.  Extracting a Mobility Model from Real User Traces , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[7]  Anders Lindgren,et al.  Probabilistic routing in intermittently connected networks , 2003, MOCO.

[8]  Rabin K. Patra,et al.  Using redundancy to cope with failures in a delay tolerant network , 2005, SIGCOMM '05.

[9]  K. N. Dollman,et al.  - 1 , 1743 .

[10]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

[11]  G. Casella,et al.  Statistical Inference , 2003, Encyclopedia of Social Network Analysis and Mining.

[12]  Yong Wang,et al.  Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet , 2002, ASPLOS X.

[13]  Magdalena Balazinska,et al.  Characterizing mobility and network usage in a corporate wireless local-area network , 2003, MobiSys '03.

[14]  Cecilia Mascolo,et al.  An ad hoc mobility model founded on social network theory , 2004, MSWiM '04.

[15]  T. Charles Clancy,et al.  Analysis of simple counting protocols for delay-tolerant networks , 2007, CHANTS '07.

[16]  Mads Haahr,et al.  Social network analysis for routing in disconnected delay-tolerant MANETs , 2007, MobiHoc '07.

[17]  Cecilia Mascolo,et al.  Adaptive routing for intermittently connected mobile ad hoc networks , 2005, Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks.

[18]  Donald F. Towsley,et al.  Performance modeling of epidemic routing , 2006, Comput. Networks.

[19]  David Kotz,et al.  Evaluating opportunistic routing protocols with large realistic contact traces , 2007, CHANTS '07.

[20]  Zygmunt J. Haas,et al.  The shared wireless infostation model: a new ad hoc networking paradigm (or where there is a whale, there is a way) , 2003, MobiHoc '03.

[21]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .