Localized sensor self-deployment with coverage guarantee
ACM SIGMOBILE Mobile Computing and Communications Review
Connectivity-Guaranteed and Obstacle-Adaptive Deployment Schemes for Mobile Sensor Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Movement and Connectivity Algorithms for Location-Based Mobile Social Networks
WIMOB '08 Proceedings of the 2008 IEEE International Conference on Wireless & Mobile Computing, Networking & Communication
Collaborative microdrones: applications and research challenges
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Simple movement control algorithm for bi-connectivity in robotic sensor networks
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
Movement control algorithms for realization of fault-tolerant ad hoc robot networks
IEEE Network: The Magazine of Global Internetworking
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In this paper we consider a cooperative application deployed over mobile nodes that aims to connect them in order to form a network where they can continuously interact together. Two types of nodes are considered, cooperative and non-cooperative. The former can move and change its location to connect itself or other nodes to the target network, whereas the latter does not move. Our objective then is to maximize the number of connected nodes in this partially cooperative network while minimizing the traveled distances performed by cooperative nodes. This leads to an NP-Hard optimization problem which is solved through several algorithms designed using clustering and assignment techniques. We also model the application as a non-linear mixed integer problem in order to compare with numerical solutions in a reasonable scale scenario. Simulation results show that algorithms based on cloudy clustering combined with a weighted cost assignment technique increase the number of connected nodes while reducing the traveled distance, compared to Force-based algorithms. Since our algorithm is designed by analyzing several strategies and by focusing on the connectivity-movement tradeoff, it achieves within 10% of the optimal numerical solution in term of traveled distance. Besides, it provides functional insights on how node movement can be controlled in such mobile cooperative networks.