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Minimum-energy broadcast and multicast in wireless networks: An integer programming approach and improved heuristic algorithms

机译:无线网络中的最低能耗广播和多播:整数编程方法和改进的启发式算法

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摘要

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal.
机译:已经提出了整数编程模型和启发式算法,以在无线自组织网络中寻找最小能量的广播和组播树。在启发式算法中,广播/组播增量功率(BIP / MIP)算法最为人所知。 BIP / MIP的理论性能已在多项研究中进行了量化。为了评估BIP / MIP和其他启发式算法的经验性能,有必要计算最佳树或最佳下限。在本文中,我们提出了一种整数编程方法以及改进的启发式算法。我们的整数编程方法包括一个新颖的整数模型和一个松弛方案。与先前提出的模型不同,我们模型的连续松弛导致最优值的非常尖锐的下界。我们的松弛方案允许对启发式算法进行性能评估,而无需计算最佳树。我们对启发式算法的贡献包括功率改进算法,连续功率调整(SPA)和改进的某些先前建议算法的时间复杂度。我们报告了广泛的数值实验。与许多其他算法相比,Algorithm SPA找到了更好的解决方案。此外,整数规划方法表明,通过算法SPA找到的树是最佳的或接近最佳的。

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