TY - GEN
T1 - Impromptu deployment of wireless relay networks
T2 - 11th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2014
AU - Chattopadhyay, Arpan
AU - Ghosh, Avishek
AU - Rao, Akhila S.
AU - Dwivedi, Bharat
AU - Anand, S. V.R.
AU - Coupechoux, Marceau
AU - Kumar, Anurag
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/2/6
Y1 - 2015/2/6
N2 - We are motivated by the problem of impromptu or as-you-go deployment of wireless sensor networks. As an application example, a person, starting from a sink node, walks along a forest trail, makes link quality measurements (with the previously placed nodes) at equally spaced locations, and deploys relays at some of these locations, so as to connect a sensor placed at some a priori unknown point on the trail with the sink node. In this paper, we report our experimental experiences with some as-you-go deployment algorithms. Two algorithms are based on Markov decision process (MDP) formulations, these require a radio propagation model. We also study purely measurement based strategies: one heuristic that is motivated by our MDP formulations, one asymptotically optimal learning algorithm, and one inspired by a popular heuristic. We extract a statistical model of the propagation along a forest trail from raw measurement data, implement the algorithms experimentally in the forest, and compare them. The results provide useful insights regarding the choice of the deployment algorithm and its parameters, and also demonstrate the necessity of a proper theoretical formulation.
AB - We are motivated by the problem of impromptu or as-you-go deployment of wireless sensor networks. As an application example, a person, starting from a sink node, walks along a forest trail, makes link quality measurements (with the previously placed nodes) at equally spaced locations, and deploys relays at some of these locations, so as to connect a sensor placed at some a priori unknown point on the trail with the sink node. In this paper, we report our experimental experiences with some as-you-go deployment algorithms. Two algorithms are based on Markov decision process (MDP) formulations, these require a radio propagation model. We also study purely measurement based strategies: one heuristic that is motivated by our MDP formulations, one asymptotically optimal learning algorithm, and one inspired by a popular heuristic. We extract a statistical model of the propagation along a forest trail from raw measurement data, implement the algorithms experimentally in the forest, and compare them. The results provide useful insights regarding the choice of the deployment algorithm and its parameters, and also demonstrate the necessity of a proper theoretical formulation.
KW - Impromptu deployment
KW - wireless relay network
UR - https://www.scopus.com/pages/publications/84925353281
U2 - 10.1109/MASS.2014.33
DO - 10.1109/MASS.2014.33
M3 - Conference contribution
AN - SCOPUS:84925353281
T3 - Proceedings - 11th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2014
SP - 232
EP - 236
BT - Proceedings - 11th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 28 October 2014 through 30 October 2014
ER -