Abstract—In view of the core node recognition in the KAD
(Kademlia), a model based on BP is presented to determine
whether a node is core node in real time. According to the result
of the measurement for KAD, some attribute characteristics of
core nodes in the network have been extracted and normalized
to obtain an attribute set with higher separable degree. An
algorithm in MatLab is designed to train the BP network until
the results are limited in a predetermined error range. In
addition, the trained BP model is adopted to determine the
tested nodes, and the results of the experiment show that the
method can judge degrees of importance of nodes in real time,
and the recognition accuracy rate is up to about 70%.
Index Terms—Back-prorogation (BP), KAD network, core
node, recognition.
Li Qiang and Tang Bo are the Institute of Communication and Signal,
CREEC, Chengdu 610031, China.
Yang Jie is with the Institute of Science and Technology, CREEC,
Chengdu 610031, China.
[PDF]
Cite: Li Qiang, Tang Bo, and Yang Jie, "Study of Recognition Algorithm for Core Node in KAD Network Based on BP Model," International Journal of Future Computer and Communication vol. 5, no. 2, pp. 108-111, 2016.
