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Risk Assessment of SLAs in Grid Computing with Predictive Probabilistic and Possibilistic Models

Christer Carlsson, Robert Fullér, Risk Assessment of SLAs in Grid Computing with Predictive Probabilistic and Possibilistic Models. In: Salvatore Greco, Ricardo Alberto Marques Pereira, Massimo Squillante, Ronald R Yager, Janusz Kacprzyk (Eds.), Preferences and Decisions: Models and Applications, Studies in Fuzziness and Soft Computing Series 257/2010, 11-29, Springer, 2010.

http://dx.doi.org/10.1007/978-3-642-15976-3_2

Abstract:

We developed a hybrid probabilistic and possibilistic technique for assessing the risk of an SLA for a computing task in a cluster/grid environment. The probability of success with the hybrid model is estimated higher than in the probabilistic model since the hybrid model takes into consideration the possibility distribution for the maximal number of failures derived from a resource provider’s observations. The hybrid model showed that we can increase or decrease the granularity of the model as needed; we can reduce the estimate of the P(S*=1) by making a rougher, more conservative, estimate of the more unlikely events of (M+1, N) node failures. We noted that M is an estimate which is dependent on the history of the nodes being used and can be calibrated to “a few” or to “many” nodes.

BibTeX entry:

@INPROCEEDINGS{inpCaFu10a,
  title = {Risk Assessment of SLAs in Grid Computing with Predictive Probabilistic and Possibilistic Models},
  booktitle = {Preferences and Decisions: Models and Applications},
  author = {Carlsson, Christer and Fullér, Robert},
  volume = {257/2010},
  series = {Studies in Fuzziness and Soft Computing Series},
  editor = {Greco, Salvatore and Pereira, Ricardo Alberto Marques and Squillante, Massimo and Yager, Ronald R and Kacprzyk, Janusz},
  publisher = {Springer},
  pages = {11-29},
  year = {2010},
  keywords = {Risk assessment, grid computing},
}

Belongs to TUCS Research Unit(s): Institute for Advanced Management Systems Research (IAMSR)

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