Name
Title | ||
|---|---|---|
Towards Scalable k-out-of-n Models for Assessing the Reliability of Large-Scale Function-as-a-Service Systems with Bayesian Networks |
Abstract | ||
|---|---|---|
Typically, Function-as-a-Service (FaaS) involves state-less replication with very large numbers of instances. The reliability of such services can be evaluated using Bayesian Networks and k-out-of-n models. However, existing k-out-of-n models do not scale to the larger number of hosts of FaaS services. Therefore, we propose a scalable k-out-of-n model in this paper with the same semantics as the standard k-out-of-n voting gates in fault trees, enabling the reliability analysis of FaaS services. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CLOUD.2019.00095 | 2019 IEEE 12th International Conference on Cloud Computing (CLOUD) |
Keywords | Field | DocType |
Reliability,Function as a Service,Bayesian Networks,Replication,k out of n,causal independence | Voting,Computer science,Bayesian network,Function as a service,Fault tree analysis,Semantics,Scale function,Distributed computing,Scalability | Conference |
ISSN | ISBN | Citations |
2159-6182 | 978-1-7281-2706-4 | 0 |
PageRank | References | Authors |
0.34 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Otto Bibartiu | 1 | 0 | 0.34 |
| Frank Dürr | 2 | 500 | 43.83 |
| Kurt Rothermel | 3 | 184 | 23.72 |
| Beate Ottenwälder | 4 | 0 | 0.68 |
| Andreas Grau | 5 | 0 | 0.68 |