{'fraction_non_alphanumeric': 0.01989467524868344, 'fraction_numerical': 0.0, 'mean_word_length': 5.218181818181818, '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 self-adaptive protocol stack for Underwater Wireless Sensor Networks

In this paper we propose the adoption of a self-adaptable cross-layer and modular Software Defined Communication Stack (SDCS) for Underwater Wireless Sensor Networks. The SDCS is a modular stack solution which is capable to run different protocols at each layer of the network stack; a new component, named policy engine, autonomously and adaptively, as the operational conditions vary, selects the protocol of each layer so as to optimize application scenario metrics of interest, e.g., packet delivery ratio, end-to-end packet latency and energy consumption. As a proof of concept, the paper presents the design and performance evaluation of a policy engine to dynamically and autonomously change the MAC protocol adopted in Underwater Wireless Sensor Networks. The best MAC protocol is chosen according to network conditions and application requirements, without any a priori knowledge. We consider three different MAC protocols running in the SDCS: CSMA, T-Lohi and DACAP that represent the class of simple, intermediate and fully negotiated MAC protocols, respectively. The performance of the three protocols are first compared via simulations considering different network conditions, such as traffic load and packet size. Then, we evaluate the ability of our policy engine to dynamically estimate the network changes and then to select accordingly the best MAC protocol without any a priori knowledge. Results show the effectiveness of our solution in that it is always able to quickly find and choose the MAC protocol that optimizes a given metric in a particular scenario by introducing a really limited overhead in the network.