System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
A taxonomy of wireless micro-sensor network models
ACM SIGMOBILE Mobile Computing and Communications Review
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Distributed regression: an efficient framework for modeling sensor network data
Proceedings of the 3rd international symposium on Information processing in sensor networks
An analysis of a large scale habitat monitoring application
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Robot and Sensor Networks for First Responders
IEEE Pervasive Computing
Analysis of Dynamic Task Allocation in Multi-Robot Systems
International Journal of Robotics Research
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Communication in a swarm of miniature robots: the e-Puck as an educational tool for swarm robotics
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
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Modeling and simulation can be powerful tools for analyzing multi-agent systems, such as networked robotic systems and sensor networks. In this paper, it is shown concretely how instances of both these elements fit into a general methodology for multi-level modeling, providing insight into system dynamics. Use of the resulting general framework is illustrated through application to a specific sample case study involving a robotic wireless sensor network engaged in an acoustic detection task. We then compare and contrast the resulting family of models, highlighting explicitly the trade-off between realism and simplicity.