{'fraction_non_alphanumeric': 0.016753926701570682, 'fraction_numerical': 0.0, 'mean_word_length': 5.248366013071895, '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 Fair-Rank Ant Colony Algorithm in Distributed Mass Storage System

In general, a distributed mass storage system is composed of a large number of computing nodes and storage nodes, allowing users to access resources transparently, without knowing where the resources are physically located. For every storage request, the storage system scheduler chooses several storage nodes from the entire storage system in order to organize a substorage system. This kind of scheduling is an NP-hard problem; to achieve the storage system's promising potential, this paper proposes a virtual subsystem quality of service scheduling model and a fair-rank ant colony algorithm. The algorithm provides special incentives to the scheduling results that include new nodes, so the new nodes will have more opportunities to participate in the scheduling system. Tests show that this algorithm performs better in the fairness and load balance than the ant colony algorithm.