Cooperative training for high density sensor and actor networks

Authors:
A. Navarra;C. M. Pinotti;V. Ravelomanana;F. Betti Sorbelli;R. Ciotti
Affiliations:
Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy;Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy;Laboratoire d'Informatique de Paris-Nord, University of Paris, France;Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy;Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy
Venue:
IEEE Journal on Selected Areas in Communications
Year:
2010

Citing 7
Cited 4

The number of neighbors needed for connectivity of wireless networks

Wireless Networks
Training a wireless sensor network

Mobile Networks and Applications
Dozer: ultra-low power data gathering in sensor networks

Proceedings of the 6th international conference on Information processing in sensor networks
Efficient corona training protocols for sensor networks

Theoretical Computer Science
Asynchronous Corona Training Protocols in Wireless Sensor and Actor Networks

IEEE Transactions on Parallel and Distributed Systems
Distributed transmit beamforming: challenges and recent progress

IEEE Communications Magazine
Wireless sensor networks: leveraging the virtual infrastructure

IEEE Network: The Magazine of Global Internetworking

Collision-free routing in sink-centric sensor networks with coarse-grain coordinates

IWOCA'10 Proceedings of the 21st international conference on Combinatorial algorithms
VIBE: An energy efficient routing protocol for dense and mobile sensor networks

Journal of Network and Computer Applications
Distributed colorings for collision-free routing in sink-centric sensor networks

Journal of Discrete Algorithms
Localization and scheduling protocols for actor-centric sensor networks

Networks

Quantified Score

Hi-index	0.07

Visualization

Abstract

Exploiting high density features of wireless sensor networks represents a challenging issue. In this context, anonymous, asynchronous and randomly distributed sensors are considered along with few devices, called actors, which are more powerful than sensors in terms of energy and transmission capabilities. The paper proposes a new distributed training protocol for coarse-grain localization purposes in high density environments. The aim is to auto-organize the sensors with respect to a virtual infrastructure centered at actors and constituted of concentric rings divided into sectors. Analytical study as well as experiments on the proposed protocol are provided. The obtained results show under which theoretical and practical settings the training process can be performed in a fast and high quality way with respect to the granularity of the required localization and the energy consumption.