Research

Modelling and analyzing the authorization and execution of video workflows


Reference:

He, L., Huang, C., Li, K., Chen, H., Sun, J., Gao, B., Duan, K. and Jarvis, S. A., 2011. Modelling and analyzing the authorization and execution of video workflows. In: 18th International Conference on High Performance Computing (HiPC), 2011. Piscataway, NJ: IEEE.

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Official URL:

http://dx.doi.org/10.1109/HiPC.2011.6152727

Abstract

It is becoming common practice to migrate signal-based video workflows to IT-based Video workflows. Video workflows have some inherent features, including: 1) necessary human involvements in video workflows introduce security and authorization concerns; 2) the frequent change of video workflow contexts requires a flexible approach to acquiring performance data; 3) the content-centric nature of video workflows, which is in contrast to the business-centric of business workflows, requires the support of scheduled activities. This paper takes the above issues into account, proposing a novel mechanism for modeling video workflow executions in cluster-based resource pools under Role-Based Authorization Control (RBAC) schemes. The Color Timed Petri-Net (CTPN) formalism is applied to construct the models. Various types of authorization constraint are modeled in this paper, and scheduled activities are also supported in the model. There is a clear interface between workflow execution and workflow authorization modules. The constructed models are then simulated and analyzed to obtain performance data, including authorization overhead, system- and application-oriented performance. Based on the model analysis, this paper further proposes the methods to improve performance in the presence of authorization policies. This work can be used to plan system capacity subject to the authorization control, and can also be used to tune performance by changing the scheduling strategy and resource capacity when it is not possible to adjust the authorization policies.

Details

Item Type Book Sections
CreatorsHe, L., Huang, C., Li, K., Chen, H., Sun, J., Gao, B., Duan, K. and Jarvis, S. A.
DOI10.1109/HiPC.2011.6152727
DepartmentsFaculty of Science > Computer Science
StatusPublished
ID Code29393

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