Iterated local optimization for minimum energy broadcast

I. Kang, R. Poovendran
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引用次数: 29

Abstract

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.
最小能量广播迭代局部优化
在我们之前的工作中,我们提出了一种高效的基于局部搜索的启发式算法,称为最大扩展扫描搜索(LESS),用于解决无线自组织或传感器网络上的最小能量广播(MEB)问题。在本文中,通过使用迭代局部优化(ILO)技术,以额外的计算复杂度为代价,进一步增强了性能。据我们所知,这种实现构成了目前已知的MEB启发式中性能最好的算法。我们通过广泛的模拟研究来支持这一说法,并与整数规划(IP)求解器获得的全局最优解进行了比较。对于20个节点以下的小型网络,由于IP求解器的实际限制,基于ILO的算法产生全局最优解的频率非常高(70%),平均性能在最优解的1.12%以内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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