{'fraction_non_alphanumeric': 0.019271948608137045, 'fraction_numerical': 0.004282655246252677, 'mean_word_length': 5.538461538461538, '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 novel source coding technique for wireless sensor networks based on Benford's law

Since its discovery in 1881, Benford's law has been verified in several application fields related to economics, physics and even in number theory. In particular, a random dataset obtained from physical measurements seems to be the best empirical example of its validity. Following this reasoning, we present a novel and fast source coding algorithm for wireless sensor measurements. In more details, the Benford's probability density distribution is exploited for Huffmann coding of measured values, considering the Benford probability density of the first digit. This results may be fast obtained assuming the Benford's law validity, without directly computing the a priori probabilities of the measured digits. Performance evaluation is provided by system simulations, comparing the obtained results with the computed a posteriori source entropy.