{'fraction_non_alphanumeric': 0.017208413001912046, 'fraction_numerical': 0.0006373486297004461, 'mean_word_length': 5.382113821138211, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A local metric for geographic routing with power control in wireless networks

We investigate the combination of distributed ge- ographic routing with transmission power control for energy efficient delivery of information in multihop wireless networks. Using realistic models for wireless channel fading as well as radio modulation and encoding, we first show that the optimal power control strategy over a given link should set the transmission power to achieve a special signal-to-noise ratio (SNR) constant that can be computed using an elegant characteristic equation. Counter-intuitively, for typical radios, this corresponds to an optimal operating point of SNR that lies in the transitional region (where packet error rates are non-negligible). We then propose a local power efficiency metric for distributed routing such that at each step the transmitter picks as the next hop the neighbor for which this metric is maximized. Through extensive simulations, we compare the performance of the proposed algorithm and globally optimal routing algorithms. We show that in randomly deployed 2-D networks, the combination of this local metric for routing with optimal power control has close performances, in terms of average power consumption under different node density settings and physical transmission power limits, to the best strategy using global network link state information. In particular, when electronic power is relatively low, the proposed algorithm can provide up to six times reduction in power usage compared to channel-unaware routing algorithms.