{'fraction_non_alphanumeric': 0.02218430034129693, 'fraction_numerical': 0.0022753128555176336, 'mean_word_length': 5.514814814814815, '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}}
The Broadcast Storm Problem in FANETs and the Dynamic Neighborhood-Based Algorithm as a Countermeasure

Flying ad hoc networks (FANETs) are a new paradigm that can overcome mission constraints of single unmanned aerial vehicles (UAVs). FANETs are composed of several UAVs that cooperate to accomplish some critical mission (i.e., hazardous area monitoring). In order to maintain UAVs coordination, all UAVs must continuously retransmit or relay messages through the wireless channel to assure that every UAV knows the FANET condition. However, when this message exchange is done arbitrarily, it may cause the broadcast storm problem, leading the wireless medium to an inoperable state. Despite some efforts reported in the literature for providing general broadcast storm problem mitigation techniques, the challenge of aggregating new information/knowledge to receivers, instead of just spreading the information in the network, has received less attention. In this paper, we not only prove that broadcast storm problem causes network contention as the number of UAVs increases but also propose the innovative dynamic neighborhood-based algorithm for the broadcast storm problem (DNA-BSP), which was developed and validated based on the outdoor experiments and computer simulations. It can mitigate the broadcast storm problem, which is a real challenge in FANETs, reducing message redundancy in more than 98%, and making message delivery more than 95% faster than in flooding scenario, outperforming classical broadcast storm mitigation techniques when applied in FANETs. Our detailed results can also guide future researches and provide useful insights for engineers planning and optimizing mission-critical mobile ad hoc network with the support of UAVs.