1 / 16

Cloud-DLS: Dynamic trusted scheduling for Cloud computing

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.

Télécharger la présentation

Cloud-DLS: Dynamic trusted scheduling for Cloud computing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Cloud-DLS: Dynamic trusted scheduling for Cloud computing Expert Systems with Application 39(2012) Wei Wang, GuosunZeng, Daizhong Tang , Jing Yao 鍾舜璽

  2. 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

  3. Introduction (cont.)

  4. Cognitive trust model based on Bayesian method • Global trust degree

  5. Direct and recommendation trust times interaction times successful times fail

  6. Direct and recommendation trust (cont.) times interaction times successful times fail

  7. Effect of time • The more recent the history information is, the more impact the factor has.

  8. Trust relationship analysis

  9. Dynamic level scheduling • Homogeneous A 2 5 B C 1 3 D

  10. Dynamic level scheduling(cont.) • Heterogeneous

  11. Cloud-DLS algorithm • Trust dynamic level A A 2 5 B C 1 3 D C

  12. Experiment result • Experiment benchmark • String Match (SM) • Reverse Index (RI) • KMeans (KM) • Similarity Score (SS) • Principal Component Analysis (PCA) • Leukocyte Tracking (LT)

  13. Experiment result (cont.) • Experiment one: the validity of trust model

  14. Experiment result (cont.) • Experiment two: Cloud-DLS vs. DLS and BSA

  15. Experiment result (cont.) • Experiment two: Cloud-DLS vs. DLS and BSA

  16. 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.

More Related