{'fraction_non_alphanumeric': 0.030139103554868624, 'fraction_numerical': 0.0015455950540958269, 'mean_word_length': 5.442786069651741, '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}}
Studying Practical Any-to-Any Backpressure Routing in Wi-Fi Mesh Networks from a Lyapunov Optimization Perspective

This paper studies practical backpressure routing strategies in WiFi-based Mesh Networks (WMN). It is practical in the sense that, unlike previous theoretical centralized algorithms, we present a distributed implementation of the algorithm with low queue complexity (i.e., one finite data queue at each node) to deal with any-to-any communications. To our knowledge, this is the first practical study based on Neely's Lyapunov optimization framework for WMNs. In fact, we propose a scalable and distributed routing policy that takes control actions based on Lyapunov's drift-plus-penalty minimization combinining local queue backlog and 1-hop geographic information. We characterize its strengths and weaknesses against network performance metrics such as throughput, delay, and fairness. By means of ns-3 simulations under different configuration setups, we study the impact of the weight of the penalty function on the network performance metrics. In addition, we show the influence of the location of the source-destination pairs in these configuration setups. Finally, we evaluate the objective function-backlog trade-off that characterizes Lyapunov optimization frameworks.