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http://localhost:8081/xmlui/handle/123456789/11733
Title: | TRUST-AWARE GRID SCHEDULING ALGORITHMS BASED ON SUBJECTIVE TRUST |
Authors: | Vasu, T. |
Keywords: | ELECTRONICS AND COMPUTER ENGINEERING;TRUST-AWARE GRID SCHEDULING;ALGORITHMS;GRID COMPUTING |
Issue Date: | 2007 |
Abstract: | Grid computing provides a virtual framework for controlled sharing of resources across institutional boundaries. Security is one major concern in any system that enables remote execution. Hence, we contend that it is essential for the Grid scheduler to consider the security implications while performing resource allocations. Recently, trust , has been recognized as an important factor for scheduling in Grid. Trust is a complex subject related to the quality of the entity such as reliability, honesty, and competence of the trusted entity. The Stability of the Grid depends on the detection of trusted and distrusted entities. Information overload, increased uncertainty and risk taking are becoming prominent while integrating trust into the Grid systems. Although a small number of trust models have been proposed- for the Grid, they largely ignore the uncertainty involved in the trust calculations and decisions. We propose a trust model for Grid systems and show how the model can be used to incorporate the trust implications into scheduling algorithms. Subjective Logic is used to calculate, and update the trust value. Subjective logic is -a belief reasoning calculus that is suitable for modeling and analyzing situations involving uncertainty and incomplete knowledge. Based on this logic, three Trust-aware scheduling algorithms are proposed to ensure the security of the executions. Simulations are performed to evaluate the performance of the algorithms. |
URI: | http://hdl.handle.net/123456789/11733 |
Other Identifiers: | M.Tech |
Research Supervisor/ Guide: | Mishra, Manoj |
metadata.dc.type: | M.Tech Dessertation |
Appears in Collections: | MASTERS' THESES (E & C) |
Files in This Item:
File | Description | Size | Format | |
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ECDG13413.pdf | 3.96 MB | Adobe PDF | View/Open |
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