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Cloud-DLS: Dynamic trusted scheduling for Cloud computing. Expert Systems with Application 39(2012) Wei Wang, Guosun Zeng , Daizhong Tang , Jing Yao 鍾舜璽. Introduction. Clouds are rapidly becoming an important platform for scientific applications.
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Cloud-DLS: Dynamic trusted scheduling for Cloud computing Expert Systems with Application 39(2012) Wei Wang, GuosunZeng, Daizhong Tang , Jing Yao 鍾舜璽
Introduction • Clouds are rapidly becoming an important platform for scientific applications. • Large scale Cloud computing infrastructure are unified computing platform which tries to connect and share all resources in the Internet • computation resource • storage resource • Information resource • knowledge resource
Cognitive trust model based on Bayesian method • Global trust degree
Direct and recommendation trust times interaction times successful times fail
Direct and recommendation trust (cont.) times interaction times successful times fail
Effect of time • The more recent the history information is, the more impact the factor has.
Dynamic level scheduling • Homogeneous A 2 5 B C 1 3 D
Dynamic level scheduling(cont.) • Heterogeneous
Cloud-DLS algorithm • Trust dynamic level A A 2 5 B C 1 3 D C
Experiment result • Experiment benchmark • String Match (SM) • Reverse Index (RI) • KMeans (KM) • Similarity Score (SS) • Principal Component Analysis (PCA) • Leukocyte Tracking (LT)
Experiment result (cont.) • Experiment one: the validity of trust model
Experiment result (cont.) • Experiment two: Cloud-DLS vs. DLS and BSA
Experiment result (cont.) • Experiment two: Cloud-DLS vs. DLS and BSA
Conclusion • The main contribution of this study to scheduling systems is that it extends the traditional formulation of the scheduling problem so that both execution time and reliability of applications are simultaneously accounted for. • Considering other aspects of security in Cloud environment is our future work.