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Formal Modeling and Analyzing the Reliability for Service Composition.

, , , and . APSEC (1), page 86-93. IEEE Computer Society, (2014)

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A Method for Analyzing and Predicting Reliability of BPEL Process., , , and . J. Softw., 4 (1): 11-18 (2009)Local versus Global Models for Just-In-Time Software Defect Prediction., , , , and . Sci. Program., (2019)Resource Constrained Profit Optimization Method for Task Scheduling in Edge Cloud., , , , and . IEEE Access, (2020)Deep Semantic Feature Learning with Embedded Static Metrics for Software Defect Prediction., , , , and . APSEC, page 244-251. IEEE, (2019)A collaborative deep learning microservice for backdoor defenses in Industrial IoT networks., , , , , , and . Ad Hoc Networks, (2022)Reparameterizable Multibranch Bottleneck Network for Lightweight Image Super-Resolution., , , , and . Sensors, 23 (8): 3963 (2023)Dynamic Trust-Based Resource Allocation Mechanism for Secure Edge Computing., , , , , and . CollaborateCom (2), volume 461 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 111-132. Springer, (2022)A Method for Modeling and Analyzing Fault-Tolerant Service Composition., , , and . APSEC, page 507-514. IEEE Computer Society, (2009)Energy and time efficient task offloading and resource allocation on the generic IoT-fog-cloud architecture., , , and . Peer-to-Peer Netw. Appl., 13 (2): 548-563 (2020)A Load-Balanced Approach to Time Efficient Resource Scheduling in SDN-Enabled Data Center., , , and . COMPSAC (2), page 216-221. IEEE Computer Society, (2018)978-1-5386-2667-2.