DocumentCode :
3691822
Title :
Modeling and evaluation of mixed redundancy strategy with instant switching in cloud-based systems
Author :
Pan He;Chun Tan;Xueliang Zhao;Zhihao Zheng
Author_Institution :
Chinese Academy of Sciences, Chongqing, China
fYear :
2015
fDate :
10/2/2015 12:00:00 AM
Firstpage :
15
Lastpage :
22
Abstract :
Mixed redundancy strategy is generally used in cloud-based systems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching process is triggered once some active nodes fail and there are available standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. A numerical method is used to solve the model and sensitivity analysis is conducted on different redundancy strategy. Illustrative examples using real-world data were presented to explain the process of calculating the probability of each state and the different kinds of availability and performance. The comparison with traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
Keywords :
"Redundancy","Cloud computing","Monitoring","Maintenance engineering","Steady-state","Transient analysis"
Publisher :
ieee
Conference_Titel :
Maintenance and Evolution of Service-Oriented and Cloud-Based Environments (MESOCA), 2015 IEEE 9th International Symposium on the
Electronic_ISBN :
2326-6937
Type :
conf
DOI :
10.1109/MESOCA.2015.7328121
Filename :
7328121
Link To Document :
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