Analyzing non-equilibrium statistical behaviors within the OLSR MANET routing protocol

Optimized Link State Routing (OLSR) is a well known proactive MANET routing protocol. Much of the existing OLSR research has been based on packet-level simulation studies in which the results are reported as the averages computed across a conducted set of Monte Carlo runs. This validity of such averaging rests on the presumption that the OLSR behaves, in terms of its network-level quality of service (QoS) measures, as an equilibrium stochastic process, (i.e., a process that converges towards a unique statistical steady state). This work empirically explores the degree to which this presumption holds for OLSR. The work shows that the degree to which OLSR exhibits non-equilibrium behaviors can be clearly influenced by adjusting its run-time tuneable parameters, (e.g., hello interval and topology control interval).

[1]  Deepali Arora,et al.  On the statistical behaviors of network-level features within MANETs , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[2]  Deepali Arora,et al.  STARS: A Framework for Statistically Rigorous Simulation-Based Network Research , 2011, 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications.

[3]  V. Wieser,et al.  A Performance of Wireless Ad-Hoc Network Routing Protocol , 2007, 2007 17th International Conference Radioelektronika.

[4]  Consolee Mbarushimana,et al.  Comparative Study of Reactive and Proactive Routing Protocols Performance in Mobile Ad Hoc Networks , 2007, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07).

[5]  You-Ze Cho,et al.  Performance Evaluation of AODV and DYMO Routing Protocols in MANET , 2010, 2010 7th IEEE Consumer Communications and Networking Conference.

[6]  Farhat Anwar,et al.  A Simulation Based Performance Analysis of Reactive Routing Protocols in Wireless Mesh Networks , 2009, 2009 International Conference on Future Networks.

[7]  Carles Gomez,et al.  Improving performance of a real ad-hoc network by tuning OLSR parameters , 2005, 10th IEEE Symposium on Computers and Communications (ISCC'05).

[8]  Ilgar Sh. Jabbarov.  On Ergodic Hypothesis , 2011 .

[9]  Fu Yongsheng,et al.  Performance Comparison and Analysis of Routing Strategies in Mobile Ad Hoc Networks , 2008, 2008 International Conference on Computer Science and Software Engineering.

[10]  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).

[11]  Saleem N. Bhatti,et al.  Tuning OLSR , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[12]  Gregory A. Hansen,et al.  The Optimized Link State Routing Protocol , 2003 .

[13]  V. R. Sarma Dhulipala,et al.  Throughput and Delay Comparison of MANET Routing Protocols , 2009 .

[14]  Hossein Ashtiani,et al.  A Comprehensive Evaluation of Routing Protocols for Ordinary and Large-Scale Wireless MANETs , 2009, 2009 IEEE International Conference on Networking, Architecture, and Storage.

[15]  Philippe Jacquet,et al.  Optimized Link State Routing Protocol (OLSR) , 2003, RFC.

[16]  Peter E. Sholander,et al.  Experimental comparison of hybrid and proactive MANET routing protocols , 2002, MILCOM 2002. Proceedings.

[17]  Tracy Camp,et al.  MANET simulation studies: the incredibles , 2005, MOCO.

[18]  Michael McGuire,et al.  Stationary distributions of random walk mobility models for wireless ad hoc networks , 2005, MobiHoc '05.

[19]  I. Kotuliak,et al.  Comparison of DSR and DYMO routing protocols in building environments , 2009, 2009 International Symposium ELMAR.

[20]  Deepali Arora,et al.  Assessing the Expected Performance of the OLSR Routing Protocol for Denser Urban Core Ad Hoc Network Deployments , 2012, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications.