Abstract
Clouds have been increasingly adopted due to primarily their elasticity and pay-as-you-go (PAYG) pricing. While many organizations outsource the entire ICT solution to public clouds like Amazon Web Services Elastic Compute Cloud (EC2), others consider occasional workload offloading (cloud bursting) due to various reasons including governance and security. In this paper, we present Cloud Bursting Scheduler (CBS), a new cloud bursting algorithm. CBS explicitly takes into account cost factors of private in-house system (or private cloud) and public cloud. In particular, CBS attempts to optimize the cost to performance ratio by offloading jobs to public cloud explicitly taking into account time-varying electricity rates with private clouds and the timeinvariant rental rate of many public clouds. Based on simulation results obtained using real workload traces, CBS saves costs of running workloads by 55% and 12% compared with costs of cloud sourcing and private cloud, respectively. It also improves resource utilization (to 89%) by judiciously (de)activating inhouse resources and dynamically provisioning cloud resources.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2017 IEEE 10th International Conference on Cloud Computing |
| Subtitle of host publication | CLOUD 2017 |
| Editors | Geoffrey C. Fox |
| Place of Publication | Piscataway, NJ |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 774-777 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781538619933 |
| DOIs | |
| Publication status | Published - 8 Sep 2017 |
| Event | 10th IEEE International Conference on Cloud Computing, CLOUD 2017 - Honolulu, United States Duration: 25 Jun 2017 → 30 Jun 2017 |
Conference
| Conference | 10th IEEE International Conference on Cloud Computing, CLOUD 2017 |
|---|---|
| Country | United States |
| City | Honolulu |
| Period | 25/06/17 → 30/06/17 |
Keywords
- cloud bursting
- Cloud computing
- cost efficiency
- energy efficiency
- scheduling