{'fraction_non_alphanumeric': 0.02091633466135458, 'fraction_numerical': 0.0, 'mean_word_length': 5.28125, '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 Framework for Named Networking on Edge AI

Edge AI is an integration of Edge Computing and Machine Learning algorithms to address concerns with how Machine Learning is currently used on the Cloud by reducing network latency, providing faster response and near-real-time classification, better control of data security and privacy, among others. However, one of its limiting factors is due to its tight integration with the Internet Protocol, which presents various concerns due to address range limitations, lack of context on the address identifiers, but more so on its host-centricity, which is a paradigm that no longer reflects how the world uses the Internet today. Because of these limitations, this study investigates the use of a different approach in communication, through Named Networking; a subset of the proposed future Internet architecture, combining concepts of Named Data Networking, Named Function Networking, and Machine Learning algorithms, to create a framework for use in Edge AI.