Constructing minimum-energy broadcast trees in wireless ad hoc networks
Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
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
IEEE Transactions on Mobile Computing
On Minimum-Energy Broadcasting in All-Wireless Networks
LCN '01 Proceedings of the 26th Annual IEEE Conference on Local Computer Networks
Ant Colony Optimization
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
IEEE Transactions on Mobile Computing
Energy-aware multicasting in wireless ad hoc networks: A survey and discussion
Computer Communications
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
A Distributed Range Assignment Protocol
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Computers & Mathematics with Applications
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In wireless ad-hoc networks, nodes are generally equipped with batteries, making energy a scarce resource. Therefore, power consumption of network operations is critical and subject to optimization. One of the fundamental problems in ad-hoc networks is broadcasting. In this work we consider the so-called minimum energy broadcast (MEB) problem, which can be stated as a combinatorial optimization problem. We develop an ant colony optimization algorithm for two scenarios: networks in which nodes are equipped with omni-directional, respectively directional, antennas. The results show that our algorithm consistently outperforms other methods for this problem.