Iterated Local Optimization for Minimum Energy Broadcast
WASHINGTON UNIV SEATTLE DEPT OF ELECTRICAL ENGINEERING
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In our prior work, we presented a highly effective local search based heuristic algorithm called the Largest Expanding Sweep Search LESS to solve the minimum energy broadcast MEB problem over wireless, ad hoc, or sensor networks. In this paper, the performance is further strengthened by using iterated local optimization ILO techniques at the cost of additional computational complexity. To the best of our knowledge, this implementation constitutes currently the best performing algorithm among the known heuristics for MEB. We support this claim through extensive simulation study, comparing with globally optimal solutions obtained by an integer programming IP solver. For small network size up to 20 nodes, which is imposed by practical limitation of the IP solver, the ILO based algorithm produces globally optimal solutions with very high frequency 70, and average performance is within 1.12 of the optimal solution.
- Numerical Mathematics
- Computer Systems
- Radio Communications