Application of a network dynamics analysis tool to mobile ad hoc networks

We present an application of the Redback network dynamics analysis tool to mobile ad hoc networks. Our goal is to understand the network properties that arise from different mobility models and to quantify how these differences impact communications. We generate input for Redback as a graph series for varying node density and speed in the random waypoint, reference point group, freeway, and Manhattan mobility models by sampling network topology in the ns-2 network simulator. The graph series are analyzed using several distance and metric measures in the Redback tool and visualized as a time series, one of the Redback output displays. We find measurable differences among mobility models that may impact mobile communications and influence protocol design.

[1]  Miro Kraetzl,et al.  Using graph diameter for change detection in dynamic networks , 2006, Australas. J Comb..

[2]  Jean-Yves Le Boudec,et al.  Perfect simulation and stationarity of a class of mobility models , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[3]  Ahmed Helmy,et al.  IMPORTANT: a framework to systematically analyze the Impact of Mobility on Performance of Routing Protocols for Adhoc Networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[4]  Kathryn Fraughnaugh,et al.  Introduction to graph theory , 1973, Mathematical Gazette.

[5]  Tracy Camp,et al.  Stationary distributions for the random waypoint mobility model , 2004, IEEE Transactions on Mobile Computing.

[6]  L. Lewis,et al.  A case-based reasoning approach to the management of faults in communications networks , 1993, Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications.

[7]  Ahmed Helmy,et al.  User Manual for IMPORTANT Mobility Tool Generators in ns-2 Simulator Version : important-1 . 0-beta , 2004 .

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

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

[10]  Xiaoyan Hong,et al.  A group mobility model for ad hoc wireless networks , 1999, MSWiM '99.

[11]  Chuanyi Ji,et al.  Intelligent network monitoring , 1995, Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing.

[12]  Ivan Stojmenovic,et al.  Simulation and Modeling of Wireless, Mobile, and AD HOC Networks , 2004 .

[13]  Albert Y. Zomaya,et al.  Modeling external network behavior by using internal measurements , 2004, J. Parallel Distributed Comput..

[14]  Horst Bunke,et al.  Similarity Measures For Hierarchical Representations Of Graphs With Unique Node Labels , 2004, Int. J. Pattern Recognit. Artif. Intell..

[15]  Kwan-Wu Chin,et al.  Implementation experience with MANET routing protocols , 2002, CCRV.

[16]  Chuanyi Ji,et al.  Proactive network fault detection , 1997, Proceedings of INFOCOM '97.

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

[18]  Hannes Hartenstein,et al.  Stochastic properties of the random waypoint mobility model: epoch length, direction distribution, and cell change rate , 2002, MSWiM '02.

[19]  Mingyan Liu,et al.  Random waypoint considered harmful , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[20]  Paul Barford,et al.  Characteristics of network traffic flow anomalies , 2001, IMW '01.

[21]  Lundy M. Lewis,et al.  A case-based reasoning approach to the management of faults in communication networks , 1993, IEEE INFOCOM '93 The Conference on Computer Communications, Proceedings.

[22]  Fan Zhang,et al.  An approach to on-line predictive detection , 2000, Proceedings 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (Cat. No.PR00728).

[23]  Wenke Lee,et al.  Proactive detection of distributed denial of service attacks using MIB traffic variables-a feasibility study , 2001, 2001 IEEE/IFIP International Symposium on Integrated Network Management Proceedings. Integrated Network Management VII. Integrated Management Strategies for the New Millennium (Cat. No.01EX470).