TY - GEN
T1 - SLA-aware resource reservation management in cloud workflows
AU - Li, Huifang
AU - Gao, Xiaochen
AU - Di, Yanjiao
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/17
Y1 - 2015/7/17
N2 - As more and more applications are deployed on the cloud platform, resource reservation guarantees the resources will be available at the needed execution time while meeting the Quality of Service (QoS) constraints. However, large proportion of resource reservation requests could degrade system performance significantly. This paper focuses on improving system performance of resource reservation on the background of cloud workflows. First, this paper argues that only critical tasks in the workflow need to be reserved in advance. Then it proposes a reservation request model with relaxed completion time and creates a fee model of the task which is specified in Service Level Agreement (SLA). Finally, we propose an admission control algorithm called Revenue Optimization Resource Reservation algorithm (RORR). It implements the control of reservation request with relaxed completion time while maximizing the revenue of cloud providers. Simulation results validate that the proposed algorithm has a progress in system utilization, requests admission ratio and cumulative revenue compared with the existing algorithm.
AB - As more and more applications are deployed on the cloud platform, resource reservation guarantees the resources will be available at the needed execution time while meeting the Quality of Service (QoS) constraints. However, large proportion of resource reservation requests could degrade system performance significantly. This paper focuses on improving system performance of resource reservation on the background of cloud workflows. First, this paper argues that only critical tasks in the workflow need to be reserved in advance. Then it proposes a reservation request model with relaxed completion time and creates a fee model of the task which is specified in Service Level Agreement (SLA). Finally, we propose an admission control algorithm called Revenue Optimization Resource Reservation algorithm (RORR). It implements the control of reservation request with relaxed completion time while maximizing the revenue of cloud providers. Simulation results validate that the proposed algorithm has a progress in system utilization, requests admission ratio and cumulative revenue compared with the existing algorithm.
KW - Cloud Workflows
KW - Resource Reservation
KW - Service Level Agreement
UR - http://www.scopus.com/inward/record.url?scp=84945564759&partnerID=8YFLogxK
U2 - 10.1109/CCDC.2015.7162673
DO - 10.1109/CCDC.2015.7162673
M3 - Conference contribution
AN - SCOPUS:84945564759
T3 - Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
SP - 4226
EP - 4231
BT - Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th Chinese Control and Decision Conference, CCDC 2015
Y2 - 23 May 2015 through 25 May 2015
ER -