@Article{jihpp.2021.016690,
AUTHOR = {Zhe Zhu, Mingjian Zhang, Yong Liu, Lan Ma, Xin Liu},
TITLE = {A Broadcast Storm Detection and Treatment Method Based on Situational  Awareness},
JOURNAL = {Journal of Information Hiding and Privacy Protection},
VOLUME = {3},
YEAR = {2021},
NUMBER = {1},
PAGES = {47--54},
URL = {http://www.techscience.com/jihpp/v3n1/42329},
ISSN = {2637-4226},
ABSTRACT = {At present, the research of blockchain is very popular, but the 
practical application of blockchain is very few. The main reason is that the 
concurrency of blockchain is not enough to support application scenarios. After 
that, applications such as Intervalue increase the concurrency of blockchain 
transactions. However, due to the problems of network bandwidth and algorithm 
performance, there is always a broadcast storm, which affects the normal use of 
nodes in the whole network. However, the emergence of broadcast storms needs 
to rely on the node itself, which may be very slow. Even if developers debug the 
corresponding code, they cannot conduct an effective test in the whole network. 
Broadcast storm problem mainly occurs in scenarios with large transaction 
volume, such as the financial industry. Due to its characteristics, the concurrency 
of transactions in the financial industry will increase at a certain time. If there is 
no effective algorithm to deal with it, the broadcast storm will be triggered and 
the whole network will be paralyzed. To solve the problem of the broadcast 
storm, this paper combines blockchain, peer-to-peer network, artificial 
intelligence, and other technologies, and proposes a broadcast storm detection 
and processing method based on situation awareness. The purpose is to cut off 
the further spread of broadcast storms from the node itself and maintain the 
normal operation of the whole network nodes.},
DOI = {10.32604/jihpp.2021.016690}
}