TY - GEN
T1 - A bio-inspired method for locating the diffusion source with limited observers
AU - Liu, Yuxin
AU - Gao, Chao
AU - She, Xinyan
AU - Zhang, Zili
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/14
Y1 - 2016/11/14
N2 - Locating the source of diffusion is a challenging problem in complex networks and has great practical significance for restraining rumors propagation and controlling epidemics spreading. An efficient locating method should have a higher locating accuracy with the minimum required information. Although existing locating methods based on observers consider the time delays of edges, they compute the time delays based on the shortest path, which may differ from the actual diffusion process. Moreover, the higher locating accuracy of traditional method with observers has a great dependence on the assumption that the propagation delays along edges follow a definite distribution such as the Gaussian distribution. In order to solve these shortcomings, this paper proposes a Physarum-inspired method to locate the diffusion source that is independence of the distribution of propagation delays. Our method quantifies the nutrient transportation process in the adaptive network evolved by Physarum, which is used to simulate the information or epidemic diffusion routes in a social network. Simulation results on various benchmark networks show that our method has a better performance in terms of error distance than that of Gaussian method without assuming the definite distribution of time delays. Together with the advantage that our method does not require the sender information of observers compared with existing methods, our method allows for a wider range of applications in the real-world networks.
AB - Locating the source of diffusion is a challenging problem in complex networks and has great practical significance for restraining rumors propagation and controlling epidemics spreading. An efficient locating method should have a higher locating accuracy with the minimum required information. Although existing locating methods based on observers consider the time delays of edges, they compute the time delays based on the shortest path, which may differ from the actual diffusion process. Moreover, the higher locating accuracy of traditional method with observers has a great dependence on the assumption that the propagation delays along edges follow a definite distribution such as the Gaussian distribution. In order to solve these shortcomings, this paper proposes a Physarum-inspired method to locate the diffusion source that is independence of the distribution of propagation delays. Our method quantifies the nutrient transportation process in the adaptive network evolved by Physarum, which is used to simulate the information or epidemic diffusion routes in a social network. Simulation results on various benchmark networks show that our method has a better performance in terms of error distance than that of Gaussian method without assuming the definite distribution of time delays. Together with the advantage that our method does not require the sender information of observers compared with existing methods, our method allows for a wider range of applications in the real-world networks.
UR - http://www.scopus.com/inward/record.url?scp=85008263861&partnerID=8YFLogxK
U2 - 10.1109/CEC.2016.7743836
DO - 10.1109/CEC.2016.7743836
M3 - 会议稿件
AN - SCOPUS:85008263861
T3 - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
SP - 508
EP - 514
BT - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
Y2 - 24 July 2016 through 29 July 2016
ER -