{'fraction_non_alphanumeric': 0.04261954261954262, 'fraction_numerical': 0.002079002079002079, 'mean_word_length': 5.13375796178344, '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}}
SPSI: A hybrid super-node election method based on information theory

By exploiting heterogeneity, the super-node paradigm can lead to improved efficiency, without compromising the decentralized nature of peer-to-peer (P2P) networks. So many relevant applications such as grids, cloud computings use super-node paradigm as the lower service. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-node selection is a challenging problem. This paper present a super-node election protocol based on self-information theory (SPSI). In SPSI, every node has a information vector (VI), and SPSI uses a weighted mean mechanism based on VI to promote the “best” nodes to super-node status. We are the first (to the best of our knowledge) to use self-information theory to select super-node. The paper also includes extensive simulation experiments to prove the efficiency, scalability and robustness of SPSI.