### 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.

Original language | English |
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Title of host publication | Studies in Fuzziness and Soft Computing |

Pages | 11-29 |

Number of pages | 19 |

Volume | 257 |

DOIs | |

Publication status | Published - 2010 |

### Publication series

Name | Studies in Fuzziness and Soft Computing |
---|---|

Volume | 257 |

ISSN (Print) | 14349922 |

### Fingerprint

### Keywords

- grid computing
- predictive possibilities
- predictive probabilities
- risk assessment

### ASJC Scopus subject areas

- Computer Science (miscellaneous)
- Computational Mathematics

### Cite this

*Studies in Fuzziness and Soft Computing*(Vol. 257, pp. 11-29). (Studies in Fuzziness and Soft Computing; Vol. 257). https://doi.org/10.1007/978-3-642-15976-3_2

**Risk assessment of SLAs in grid computing with predictive probabilistic and possibilistic models.** / Carlsson, Christer; Fullér, R.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*Studies in Fuzziness and Soft Computing.*vol. 257, Studies in Fuzziness and Soft Computing, vol. 257, pp. 11-29. https://doi.org/10.1007/978-3-642-15976-3_2

}

TY - CHAP

T1 - Risk assessment of SLAs in grid computing with predictive probabilistic and possibilistic models

AU - Carlsson, Christer

AU - Fullér, R.

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - grid computing

KW - predictive possibilities

KW - predictive probabilities

KW - risk assessment

UR - http://www.scopus.com/inward/record.url?scp=77956384004&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77956384004&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-15976-3_2

DO - 10.1007/978-3-642-15976-3_2

M3 - Chapter

AN - SCOPUS:77956384004

SN - 9783642159756

VL - 257

T3 - Studies in Fuzziness and Soft Computing

SP - 11

EP - 29

BT - Studies in Fuzziness and Soft Computing

ER -