In this paper, we investigate the transmission-power assignment problem for κ-connected Mobile Ad hoc NET-works (MANETs), the problem of optimizing the lifetime of a MANET at a given degree κ of connectivity by minimizing power consumption. Our proposed solution is fully distributed and uses a model-based transmission power adaptation strategy based on model-predictive control. Specifically, a stochastic model of the network is used by a state estimator to predict the network's future degree of connectivity and remaining energy. The predicted states are used by an optimizer to derive an optimal transmission power assignment sequence which tracks the desired connectivity level κ. while minimizing energy consumption. Our experimental results on a simulated wireless sensor network comprising 100 mobile nodes reveals that our localized topology control algorithm provides an almost identical control policy to that of a globalized scheme which is solving a fully observable problem. The difference, of course, is in the scalability of our localized solution, which requires much less communication bandwidth and energy than the globalized approach. © 2008 IEEE.
Riganelli, O., Grosu, R., Das, S., Ramakrishnan, C., Smolka, S. (2008). Power optimization in fault-tolerant mobile ad hoc networks. In Proceedings of IEEE International Symposium on High Assurance Systems Engineering (pp.362-370) [10.1109/HASE.2008.12].
Power optimization in fault-tolerant mobile ad hoc networks
Riganelli, Oliviero
;
2008
Abstract
In this paper, we investigate the transmission-power assignment problem for κ-connected Mobile Ad hoc NET-works (MANETs), the problem of optimizing the lifetime of a MANET at a given degree κ of connectivity by minimizing power consumption. Our proposed solution is fully distributed and uses a model-based transmission power adaptation strategy based on model-predictive control. Specifically, a stochastic model of the network is used by a state estimator to predict the network's future degree of connectivity and remaining energy. The predicted states are used by an optimizer to derive an optimal transmission power assignment sequence which tracks the desired connectivity level κ. while minimizing energy consumption. Our experimental results on a simulated wireless sensor network comprising 100 mobile nodes reveals that our localized topology control algorithm provides an almost identical control policy to that of a globalized scheme which is solving a fully observable problem. The difference, of course, is in the scalability of our localized solution, which requires much less communication bandwidth and energy than the globalized approach. © 2008 IEEE.File | Dimensione | Formato | |
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