{'fraction_non_alphanumeric': 0.017529215358931552, 'fraction_numerical': 0.0, 'mean_word_length': 6.136904761904762, '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}}
QUALITY-OF-SERVICE ADAPTIVE CONTROL OF MULTIMEDIA SERVICES IN SHORT-TERM RESOURCE RESERVATION NETWORKS

ABSTRACT Present multimedia services are provided through a heterogeneous set of networks. Because of the heterogeneity of the networks, long-term resource availability guarantees are difficult to obtain. Consequently, even if the resource requirements throughout the service could be accurately mapped, it would not be feasible to provide overall performance guarantees. Application adaptation arises as an appropriate solution for quality-of-service assurance in such dynamic service infrastructures. Application adaptation basically involves adapting application characteristics according to the network resource availability. We formulate the problem of adaptation of multimedia applications to network infrastructure as well as to user- and application-imposed constraints and preferences. We benefit from the good approximation, identification, and control capabilities of recurrent high-order neural networks and we introduce an algorithm that guarantees the resource constraints of the network infrastructure will not be violated while maintaining the user and application requirements.