The algebraic degree of geometric optimization problems
Discrete & Computational Geometry
Making Sensor Networks Practical with Robots
Pervasive '02 Proceedings of the First International Conference on Pervasive Computing
Perpetual environmentally powered sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Sensor replacement using mobile robots
Computer Communications
Distributed facility location algorithms for flexible configuration of wireless sensor networks
DCOSS'07 Proceedings of the 3rd IEEE international conference on Distributed computing in sensor systems
A local facility location algorithm for sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Adjusting the cluster size based on the distance from the sink
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
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Energy management is one of the main hurdles in the quest for autonomous and reliable sensor networks. We present a cluster-based model for energy management in networks with static sensors and mobile robots that act as maintenance entities. The objective is to increase network availability by recharging, replacing or redeploying "depleted" sensors with the help of mobile robots. The problem is to find a network partition where (1) workload is balanced (i.e. an equipartition) and (2) the movements of the maintenance robots in their partition is minimized. This should be done efficiently at least for the weakest elements of the system, the sensors; that is (3) the number of sensor communications should be kept small. While finding the optimal partition is a NP-hard problem, we show a simple and efficient distributed solution that provides partitions of remarkable quality. The simulation results show a rapid progression towards convergence with the quality of the partition similar to a centralized clustering benchmark (K-means). The analysis of our solutions also shows that sensor message cost remains constant as the size of the network increases.