`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
Competitive Environments Evolve Better Solutions for Complex Tasks
Proceedings of the 5th International Conference on Genetic Algorithms
GA-based Performance Analysis of Network Protocols
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
TOSSIM: accurate and scalable simulation of entire TinyOS applications
Proceedings of the 1st international conference on Embedded networked sensor systems
Performance evaluation of routing protocols for ad hoc wireless networks
Mobile Networks and Applications
MicroGP—An Evolutionary Assembly Program Generator
Genetic Programming and Evolvable Machines
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
MoteLab: a wireless sensor network testbed
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Improving wireless simulation through noise modeling
Proceedings of the 6th international conference on Information processing in sensor networks
Fidelity and yield in a volcano monitoring sensor network
OSDI '06 Proceedings of the 7th symposium on Operating systems design and implementation
On the lifetime of wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Empirical study of a medical sensor application in an urban emergency department
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
T-check: bug finding for sensor networks
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Anquiro: enabling efficient static verification of sensor network software
Proceedings of the 2010 ICSE Workshop on Software Engineering for Sensor Network Applications
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
The impact of network topology on collection performance
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
Evolutionary Optimization: the GP toolkit
Evolutionary Optimization: the GP toolkit
On software verification for sensor nodes
Journal of Systems and Software
Towards a model checker for Nesc and wireless sensor networks
ICFEM'11 Proceedings of the 13th international conference on Formal methods and software engineering
Quo vadis, evolutionary computation?: on a growing gap between theory and practice
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
An evolutionary framework for routing protocol analysis in wireless sensor networks
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
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The analysis of worst-case behavior in wireless sensor networks is an extremely difficult task, due to the complex interactions that characterize the dynamics of these systems. In this paper, we present a new methodology for analyzing the performance of routing protocols used in such networks. The approach exploits a stochastic optimization technique, specifically an evolutionary algorithm, to generate a large, yet tractable, set of critical network topologies; such topologies are then used to infer general considerations on the behaviors under analysis. As a case study, we focused on the energy consumption of two well-known ad hoc routing protocols for sensor networks: the multi-hop link quality indicator and the collection tree protocol. The evolutionary algorithm started from a set of randomly generated topologies and iteratively enhanced them, maximizing a measure of ''how interesting'' such topologies are with respect to the analysis. In the second step, starting from the gathered evidence, we were able to define concrete, protocol-independent topological metrics which correlate well with protocols' poor performances. Finally, we discovered a causal relation between the presence of cycles in a disconnected network, and abnormal network traffic. Such creative processes were made possible by the availability of a set of meaningful topology examples. Both the proposed methodology and the specific results presented here - that is, the new topological metrics and the causal explanation - can be fruitfully reused in different contexts, even beyond wireless sensor networks.