Low power systems for wireless microsensors
ISLPED '96 Proceedings of the 1996 international symposium on Low power electronics and design
CMOS front end components for micropower RF wireless systems
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Wireless integrated network sensors
Communications of the ACM
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
Improving the Scalability of Multi-Agent Systems
Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
A method for decentralized clustering in large multi-agent systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Distributed Sensor Networks: A Multiagent Perspective
Distributed Sensor Networks: A Multiagent Perspective
Scaling Teamwork to Very Large Teams
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Networking issues in wireless sensor networks
Journal of Parallel and Distributed Computing
Task allocation via self-organizing swarm coalitions in distributed mobile sensor network
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Centibots: very large scale distributed robotic teams
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Simulating BDI-Based Wireless Sensor Networks
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
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Large-scale sensor networks are becoming more present in our life then ever. Such an environment could be a cellular network, an array of fire detection sensors, an array of solar receptors, and so on. As technology advances, opportunities arise to form large-scale cooperative systems in order to solve larger problems in an efficient way. As more large-scale systems are developed, there is a growing need to (i) measure the hardness of a given large-scale sensor network problem, (ii) compare a given system to other large-scale sensor networks in order to extract a suitable solution, (iii) predict the performance of the solution, and (iv) derive the value of each system property from the desired performance of the solution, the problem constraints, and the user's preferences. The following research proposes a novel system term, the coverage density, to define the hardness of a large-scale sensor network. This term can be used to compare two instances of large-scale sensor networks in order to find the suitable solutions for a given problem. Given a coverage density of a system, one may predict the solution performance and use it jointly with the preference and the constraints to derive the value of the system's properties.