TY - GEN
T1 - Toward cost efficient cloud bursting
AU - Pasdar, Amirmohammad
AU - Lee, Young Choon
AU - Almi’ani, Khaled
PY - 2019
Y1 - 2019
N2 - While private clouds are still widely adopted due primarily to privacy and security reasons, they are often less resilient with fluctuating workloads compared to public clouds. Workload surges in private clouds can be dealt with by offloading some workload/jobs to public clouds; this is referred to as cloud bursting. Although the dynamic use of public clouds is claimed to be cost efficient, the actual realization of such cost efficiency is highly dependent on judicious scheduling decisions. In this paper, we present Cost Efficient Cloud Bursting Scheduler (CECBS) as a new scheduling framework that optimizes cost efficiency while preserving privacy by taking advantage of benefits of each of two cloud types. In particular, CECBS schedules jobs taking into account (1) public cloud pricing policy (billing cycle), (2) privacy of data/job and (3) local electricity rates for private clouds. Based on simulation results obtained from real workload traces, CECBS achieves 20% cost savings on average compared with costs of Resource Management Service (RMS).
AB - While private clouds are still widely adopted due primarily to privacy and security reasons, they are often less resilient with fluctuating workloads compared to public clouds. Workload surges in private clouds can be dealt with by offloading some workload/jobs to public clouds; this is referred to as cloud bursting. Although the dynamic use of public clouds is claimed to be cost efficient, the actual realization of such cost efficiency is highly dependent on judicious scheduling decisions. In this paper, we present Cost Efficient Cloud Bursting Scheduler (CECBS) as a new scheduling framework that optimizes cost efficiency while preserving privacy by taking advantage of benefits of each of two cloud types. In particular, CECBS schedules jobs taking into account (1) public cloud pricing policy (billing cycle), (2) privacy of data/job and (3) local electricity rates for private clouds. Based on simulation results obtained from real workload traces, CECBS achieves 20% cost savings on average compared with costs of Resource Management Service (RMS).
UR - http://www.scopus.com/inward/record.url?scp=85076361969&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-33702-5_23
DO - 10.1007/978-3-030-33702-5_23
M3 - Conference proceeding contribution
AN - SCOPUS:85076361969
SN - 9783030337018
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 299
EP - 313
BT - Service-Oriented Computing
A2 - Yangui, Sami
A2 - Bouassida Rodriguez, Ismael
A2 - Drira, Khalil
A2 - Tari, Zahir
PB - Springer
CY - Switzerland
T2 - 17th International Conference on Service-Oriented Computing, ICSOC 2019
Y2 - 28 October 2019 through 31 October 2019
ER -