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

Christer Carlsson, Robert Fullér, Predictive Probabilistic and Possibilistic Models Used for Risk Assessment of SLAs in Grid Computing. In: Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems: Applications, Communications in Computer and Information Science 81/2010, Springer, Springer, 2010.

http://dx.doi.org/10.1007/978-3-642-14058-7_77

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 o f 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{inpCaFu10b,
  title = {Predictive Probabilistic and Possibilistic Models Used for Risk Assessment of SLAs in Grid Computing},
  booktitle = {Information Processing and Management of Uncertainty in Knowledge-Based Systems: Applications},
  author = {Carlsson, Christer and Fullér, Robert},
  volume = {81/2010},
  series = {Communications in Computer and Information Science},
  editor = {Hüllermeier, Eyke and Kruse, Rudolf and Hoffmann, Frank},
  publisher = {Springer},
  pages = {Springer},
  year = {2010},
  keywords = {Hybrid risk assessment, grid computing},
}

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

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