IEEE Transactions on Software Engineering
Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Energy-aware adaptation for mobile applications
Proceedings of the seventeenth ACM symposium on Operating systems principles
Intelligent mobile agents in large distributed autonomous cooperative systems
Journal of Systems and Software - Special issue on invited articles on top systems and software engineering scholars
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Concurrency
Entropy-based sensor selection heuristic for target localization
Proceedings of the 3rd international symposium on Information processing in sensor networks
Decentralized Reactive Clustering for Collaborative Processing in Sensor Networks
ICPADS '04 Proceedings of the Parallel and Distributed Systems, Tenth International Conference
Journal of Parallel and Distributed Computing
Collaborative in-network processing for target tracking
EURASIP Journal on Applied Signal Processing
Multiresolution data integration using mobile agents in distributedsensor networks
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Computing paradigm plays an important and fundamental role in collaborative processing in Wireless Sensor Networks (WSN). The client/server based paradigm and the mobile agent based paradigm are two popular computing models used to facilitate collaboration among sensor nodes. We study the key problem of determining mobile agent itinerary for collaborative processing and models the Dynamic Mobile Agent Planning (DMAP) problem. We then present two itinerary planning algorithms with the goal of maximising the information extracted while keeping resource usage to a minimum. The ISMAP determines the itinerary before dispatching the mobile agent while the IDMAP algorithm selects the route on the fly. We design three metrics (energy consumption, network lifetime, and the number of hops) and use simulation tools to quantitatively measure the performance of different itinerary planning algorithms. Simulation results show considerable improvement over the ISMAP using the IDMAP itinerary algorithm.