Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
A wireless sensor network For structural monitoring
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Agile cargo tracking using mobile agents
Proceedings of the 3rd international conference on Embedded networked sensor systems
Mobile agent middleware for sensor networks: an application case study
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
An intelligent agent for fault reconnaissance in sensor networks
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Fault reconnaissance agent for sensor networks
Mobile Information Systems
Distributed Agent Based Interoperable Virtual EMR System for Healthcare System Integration
Journal of Medical Systems
WSN in cyber physical systems: Enhanced energy management routing approach using software agents
Future Generation Computer Systems
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Wireless sensor networks are often difficult to program and unable to adapt to a changing environment. Mobile agent middleware promises to address both concerns by providing higher-level programming abstractions and the ability to inject new agents into a preexisting network. The unique characteristics of wireless sensor networks like resource scarcity and emphasis on spatial locality require new algorithms for controlling agent behavior. This paper presents a procedure for one specific behavior: network exploration. Network exploration is needed by many tasks ranging from simple data collection to network health monitoring. Our proposed procedure uses a genetic algorithm to determine the number of agents and their itineraries, followed by techniques for in-network adaptation to unpredictable situations like node failure. This paper presents a genetic algorithm and its adaptation strategies. The procedure is evaluated using a wireless sensor network consisting of 25 Mica2 motes running Agilla, a mobile agent middleware for wireless sensor networks.