Exploring Content Dependencies to Better Balance Performance and Freshness in Web Database Applications

Author(s):  
Stavros Papastavrou ◽  
Panos K. Chrysanthis ◽  
George Samaras
2004 ◽  
Vol 29 (5) ◽  
pp. 1-10 ◽  
Author(s):  
Yuetang Deng ◽  
Phyllis Frankl ◽  
Jiong Wang

2013 ◽  
Vol 17 (5) ◽  
pp. 969-995 ◽  
Author(s):  
Stavros Papastavrou ◽  
Panos K. Chrysanthis ◽  
George Samaras

2008 ◽  
Author(s):  
Megan K. Crane ◽  
Lisa J. Storrie-Lombardi ◽  
Nancy A. Silbermann ◽  
Luisa M. Rebull

Author(s):  
Shraddha Pankaj Phansalkar ◽  
Ajay Dani

Contemporary web-applications are deployed on the cloud data-stores for realizing requirements like low latency and high scalability. Although cloud-based database applications exhibit high performance with these features, they compromise on the weaker consistency levels. Rationing the consistency guarantees of an application is a necessity to achieve the augmented metrics of application performance. The proposed work is a paradigm shift from monotonic transaction consistency to selective data consistency in web database applications. The selective data consistency model leverages consistency of critical data-objects and leaves consistency of non-critical data-objects to underlying cloud data-store; it is called selective consistency and it results in better performance of the cloud-based applications. The consistency of the underlying data-object is defined from user-perspective with a user-friendly consistency metric called Consistency Index (CI). The selective data consistency model is implemented on a cloud data-store with OLTP workload and the performance is gauged.


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