{'fraction_non_alphanumeric': 0.007215007215007215, 'fraction_numerical': 0.0, 'mean_word_length': 5.733009708737864, '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}}
Context information provisioning in tuple spaces

The doctoral research work presented in this paper explores a novel context provisioning approach based on tuple spaces. Context information is a key part of pervasive computing applications and the increasing amount of potential context information sources makes distributed context provisioning system design a key research issue for pervasive computing. Context aware applications need to be provided with the context information they require and the distributed systems that support these pervasive computing applications must do so in a simple, concurrent and highly scalable way. We believe that tuple spaces and the alternative communication and coordination paradigms they promote are well suited for this task. This paper analyses both the viability of using tuple spaces to support context provisioning systems and the benefits it provides. The theoretical model and the basic assumptions behind this research work is presented together with the simulation framework developed in order to validate that theoretical model. This simulation framework aims at measuring the execution of complex context provisioning systems to help model their performance and optimize the context provisioning process. Several simulation experiments have been conducted to quantify the performance of the system, with encouraging initial results.