首页|Fault Diagnosis for Service Composition by Spiking Neural P Systems with Colored Spikes

Fault Diagnosis for Service Composition by Spiking Neural P Systems with Colored Spikes

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A variety of web services have emerged with the rapid development of the Internet.These services are often of a single function.The value-added services can be achieved by combing with multiple services.The processing speed and stability of existing methods in service composition were not very well and seldom consider the fault diagnosis and handling methods for the service,which results in a greater probability of the service composition failure at run time.We use spiking neural P systems with colored spikes to model the fault of available service,component,and connector in the service composition.The proposed model can be used to locate a fault and handle it correctly when the service combination fails,the advantage of efficiency and stability of proposed method has been proved by comparing with the method of Petri net.

Spiking neural P system with colored spikesService compositionFault handling

PANG Shanchen、WANG Min、QIAO Sibo、WANG Xun、CHEN Hongqi

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College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, China

This work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaKey Research and Development Program of Shandong ProvinceNatural Science Foundation of Shandong ProvinceFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesTalent introduction project of China University of Petroleum

6157252361873280615025356157252261672033616722482017GGX10147ZR2017MF00416CX02006A16CX02008A18CX02152A2017010054

2019

10.1049/cje.2019.06.023

中国电子杂志(英文版)

中国电子杂志(英文版)

CSTPCDCSCDSCIEI
ISSN：1022-4653
年,卷(期)：2019.28(5)
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