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Shadow Sensitive SWIFT: A Commit Protocol for Advanced Data Warehouses

Shadow Sensitive SWIFT: A Commit Protocol for Advanced Data Warehouses
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Author(s): Udai Shanker (Madan Mohan Malviya Engineering College, India), Abhay N. Singh (Madan Mohan Malviya Engineering College, India), Abhinav Anand (Madan Mohan Malviya Engineering College, India)and Saurabh Agrawal (Madan Mohan Malviya Engineering College,, India)
Copyright: 2011
Pages: 21
Source title: Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains
Source Author(s)/Editor(s): A.V. Senthil Kumar (CMS College of Science and Commerce, India)
DOI: 10.4018/978-1-60960-067-9.ch007

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Abstract

This chapter proposes Shadow Sensitive SWIFT commit protocol for Distributed Real Time Database Systems (DRTDBS), where only abort dependent cohort having deadline beyond a specific value (Tshadow_creation_time) can forks off a replica of itself called a shadow, whenever it borrows dirty value of a data item. The new dependencies Commit-on-Termination external dependency between final commit operations of lender and shadow of its borrower and Begin-on-Abort internal dependency between shadow of borrower and borrower itself are defined. If there is serious problem in commitment of lender, execution of borrower is started with its shadow by sending YES-VOTE message piggy bagged with the new result to its coordinator after aborting it and abort dependency created between lender and borrower due to update-read conflict is reversed to commit dependency between shadow and lender with read-update conflict and commit operation governed by Commit-on-Termination dependency. The performance of Shadow Sensitive SWIFT is compared with shadow PROMPT, SWIFT and DSS-SWIFT commit protocols (Haritsa, Ramamritham, & Gupta, 2000; Shanker, Misra, & Sarje, 2006; Shanker, Misra, Sarje, & Shisondia, 2006) for both main memory resident and disk resident databases with and without communication delay. Simulation results show that the proposed protocol improves the system performance up to 5% as transaction miss percentage.

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