Abstract
For economically provisioning services, service providers can purchase combinations of reserved and on-demand instances from Infrastructure-as-a-Service (IaaS) clouds. These different billing options bring challenges to service providers on how to purchase instances optimally to ensure quality of service (QoS) while maximizing revenue. In order to ensure QoS and maximize average revenue, a service provider can purchase fixed number of reserved instances to meet the base workload of its service system, and then dynamically purchase on-demand instances to satisfy the service requests beyond its base workload. However, the random, dynamic, and uncertain nature of service request arrivals makes it difficult for service providers to determine the optimal number of on-demand instances to be purchased dynamically. To solve the above problems, in this paper, we propose an online scheduling algorithm based on the theory of Lyapunov optimization and explore the concept of capacity region and queue stability to ensure QoS. Our online algorithm dynamically purchases on-demand instances and schedules jobs to run according to the bidding price of users without requiring the future workload information. Through our proposed online scheduling algorithm, service providers can both ensure QoS and maximize average revenue, and make a trade-off between them. Simulation results show that our algorithm can effectively achieve bi-objective optimization of maximizing time average revenue as well as ensuring QoS.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
