Open AccessBusiness Anomaly Detection Based on QoS Benchmark of Resource-service Chain in Collaborative Task
Author(s) -
Haibo Li,
Juncheng Tong,
Zheng Zhang,
Yongbo Yu
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022135
Subject(s) - benchmark (surveying) , quality of service , anomaly detection , cluster analysis , resource (disambiguation) , computer science , task (project management) , service (business) , anomaly (physics) , feature (linguistics) , data mining , distributed computing , computer network , artificial intelligence , business , systems engineering , engineering , geology , linguistics , philosophy , physics , geodesy , condensed matter physics , marketing
To detect business anomaly caused by resource services in collaborative task, an approach based on QoS benchmark of resource-service chain is presented. Firstly, taking QoS of resource services as feature, the QoS benchmarks are obtained by clustering the relationships between the features of resource services in resource service chains. Then, thresholds of QoS benchmarks are calculated. A dynamic calibration strategy to the threshold is used to perform online detection of business anomaly in global and local views of a collaborative task. Finally, experiments and case studies show that the proposed approach has a high accuracy rate for business anomaly detection.