Does mobility matter?

In modern society, wireless devices are commonly carried by humans. The wireless communication is therefore affected by pedestrian mobility in urban outdoor and indoor spaces which is the scenario we consider in this work. Many of the mobility models currently used for evaluating wireless communication systems have poor resemblance to reality. Although advances have recently been made, there is still a lack of understanding on which elements of mobility affect system performance. In the civil-engineering field of transport and urban planning there exist advanced pedestrian mobility models, used for designing and dimensioning public spaces for pedestrian crowds and emergency evacuation. These models capture micro-mobility of pedestrians better than most mobility models used in mobile networking since the application domain requires that they realistically capture node interactions with its physical environment as well as other nodes. In this work we use Legion Studio, a commercial simulator, to explore which elements of pedestrian mobility are important with respect to system performance and how sensitive the connectivity metrics of nodes are to input mobility parameters. These studies give insight into whether relatively simple mobility models suffice for evaluating wireless systems. Furthermore, they contribute to our understanding of which parameters are important for modelling mobility and the accuracy in which these parameters need to be estimated to give dependable results.

[1]  Gunnar Karlsson,et al.  A mobility model for pedestrian content distribution , 2009, SimuTools.

[2]  Kevin C. Almeroth,et al.  Towards realistic mobility models for mobile ad hoc networks , 2003, MobiCom '03.

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

[4]  Pan Hui,et al.  Pocket switched networks and human mobility in conference environments , 2005, WDTN '05.

[5]  Kristján Valur Jónsson,et al.  Opportunistic networking in OMNeT , 2008, Simutools 2008.

[6]  Mario Gerla,et al.  BlueTorrent: Cooperative Content Sharing for Bluetooth Users , 2007, Fifth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom'07).

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

[8]  Ólafur Ragnar Helgason,et al.  Opportunistic networking in OMNeT++ , 2008, SimuTools.

[9]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

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

[11]  J. L. Berrou,et al.  Calibration and validation of the Legion simulation model using empirical data , 2007 .

[12]  Arun Venkataramani,et al.  DTN routing as a resource allocation problem , 2007, SIGCOMM '07.

[13]  Cecilia Mascolo,et al.  A community based mobility model for ad hoc network research , 2006, REALMAN '06.

[14]  Gunnar Karlsson,et al.  Delay-Tolerant Broadcasting , 2006, IEEE Transactions on Broadcasting.

[15]  Ahmed Helmy,et al.  The IMPORTANT framework for analyzing the Impact of Mobility on Performance Of RouTing protocols for Adhoc NeTworks , 2003, Ad Hoc Networks.

[16]  Serge P. Hoogendoorn,et al.  Pedestrian route-choice and activity scheduling theory and models , 2004 .

[17]  Louise E. Moser,et al.  An analysis of the optimum node density for ad hoc mobile networks , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[18]  Pan Hui,et al.  Impact of Human Mobility on the Design of Opportunistic Forwarding Algorithms , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[19]  Injong Rhee,et al.  SLAW: A New Mobility Model for Human Walks , 2009, IEEE INFOCOM 2009.

[20]  Jörg Ott,et al.  Working day movement model , 2008, MobilityModels '08.

[21]  Hirozumi Yamaguchi,et al.  Getting urban pedestrian flow from simple observation: realistic mobility generation in wireless network simulation , 2005, MSWiM '05.

[22]  C. Diot,et al.  Experimenting with Opportunistic Networking , 2009 .

[23]  Henning Schulzrinne,et al.  Effects of power conservation, wireless coverage and cooperation on data dissemination among mobile devices , 2001, MobiHoc '01.

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

[25]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[26]  S. Chong,et al.  SLAW : A Mobility Model for Human Walks , 2009 .