An Evolutionary Framework for Routing Protocol Analysis in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are widely adopted for applications ranging from surveillance to environmental monitoring. While powerful and relatively inexpensive, they are subject to behavioural faults which make them unreliable. Due to the complex interactions between network nodes, it is difficult to uncover faults in a WSN by resorting to formal techniques for verification and analysis, or to testing. This paper proposes an evolutionary framework to detect anomalous behaviour related to energy consumption in WSN routing protocols. Given a collection protocol, the framework creates candidate topologies and evaluates them through simulation on the basis of metrics measuring the radio activity on nodes. Experimental results using the standard Collection Tree Protocol show that the proposed approach is able to unveil topologies plagued by excessive energy depletion over one or more nodes, and thus could be used as an offline debugging tool to understand and correct the issues before network deployment and during the development of new protocols.

[1]  Philip Levis,et al.  Improving Wireless Simulation Through Noise Modeling , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[2]  Gian Franco Sacco,et al.  Application of genetic algorithm for flight system verification and validation , 2009, 2009 IEEE Aerospace conference.

[3]  Giovanni Squillero,et al.  A Framework for Automated Detection of Power-related Software Errors in Industrial Verification Processes , 2010, J. Electron. Test..

[4]  Philip Levis,et al.  Collection tree protocol , 2009, SenSys '09.

[5]  Andreas Tolk,et al.  Intelligence-Based Systems Engineering , 2011 .

[6]  François Ingelrest,et al.  The hitchhiker's guide to successful wireless sensor network deployments , 2008, SenSys '08.

[7]  Peng Li,et al.  T-check: bug finding for sensor networks , 2010, IPSN '10.

[8]  Klaus Wehrle,et al.  KleeNet: discovering insidious interaction bugs in wireless sensor networks before deployment , 2010, IPSN '10.

[9]  Koen Langendoen,et al.  Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[10]  Daniel Kroening,et al.  A Survey of Automated Techniques for Formal Software Verification , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[11]  Giovanni Squillero,et al.  Evolutionary Optimization: the µGP toolkit , 2011 .

[12]  Doina Bucur,et al.  On software verification for sensor nodes , 2011, J. Syst. Softw..

[13]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[14]  Oliver Obst,et al.  Wireless Sensor Network Anomalies: Diagnosis and Detection Strategies , 2011 .

[15]  Jonathan W. Hui,et al.  T 2 : A Second Generation OS For Embedded Sensor Networks , 2005 .

[16]  Sven Schellenberg,et al.  Experiments in applying evolutionary algorithms to software verification , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[17]  Luciano Baresi,et al.  Anquiro: enabling efficient static verification of sensor network software , 2010, SESENA '10.