Constructing minimum-energy broadcast trees in wireless ad hoc networks
Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing
Minimum-energy broadcast in all-wireless networks: NP-completeness and distribution issues
Proceedings of the 8th annual international conference on Mobile computing and networking
Minimum-energy broadcasting in static ad hoc wireless networks
Wireless Networks
On Minimum-Energy Broadcasting in All-Wireless Networks
LCN '01 Proceedings of the 26th Annual IEEE Conference on Local Computer Networks
Iterated Local Optimization for Minimum Energy Broadcast
WIOPT '05 Proceedings of the Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Energy-aware multicasting in wireless ad hoc networks: A survey and discussion
Computer Communications
Nested Partitioning for the Minimum Energy Broadcast Problem
Learning and Intelligent Optimization
Evolutionary local search for the minimum energy broadcast problem
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
The hyper-cube framework for ant colony optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computers & Mathematics with Applications
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Abstract: The classical minimum energy broadcast (MEB) problem in wireless adhoc networks, which is well-studied in the scientific literature, considers an antenna model that allows the adjustment of the transmission power to any desired real value from zero up to the maximum transmission power. However, when specifically considering sensor networks, a look at the currently available hardware shows that this antenna model is not very realistic. A first contribution of this work is therefore the re-formulation of the MEB problem for an antenna model that is realistic for sensor networks. In this antenna model transmission power levels are chosen from a finite set of possible ones. The second contribution concerns the adaptation of ant colony optimization, a current state-of-the-art algorithm for the classical MEB problem, to the more realistic problem version. The obtained results show that the advantage of ant colony optimization over classical heuristics even grows when the number of possible transmission power levels decreases.