Abstract
Cloud computing realizes a utility computing paradigm by offering shared resources through an Internet-based computing. However, how a system control can enhance profit and simultaneously satisfy the service level agreements (SLAs) has become one of the major interests for cloud providers. In this paper, a cloud server farm provided with finite capacity is modeled as anM/M/R/Kqueuing system. Revenue losses are estimated according to the system controls and impatient customer behaviors. Three important issues are solved in this paper. First, a profit function is developed in which both the system blocking loss and the user abandonment loss are evaluated in total revenue. A tradeoff between meeting system performances and reducing operating costs is conducted. Second, the effects of system capacity control and utilization on various performances of waiting time, loss probability, and final arrival rate are demonstrated. Finally, the proposed optimal profit control (OPC) policy allows a cloud provider to make the optimal decision in the number of servers and system capacity, so as to maximize profit. As compared to a system without applying the OPC policy, enhancing providers’ profit and improving system performances can be obtained.
Highlights
Cloud computing is a popular service paradigm recently in an information technology (IT) industry that offers infrastructure, platform, software, and so forth as services
(iii) Simulations show that the optimal decision making in server quantity and system capacity to maximize profit within a loss probability guarantee can be obtained by applying the proposed optimal profit control (OPC) policy
Developing a successful cloud service system depends on accurate performance evaluations and effective system controls
Summary
Cloud computing is a popular service paradigm recently in an information technology (IT) industry that offers infrastructure, platform, software, and so forth as services. Mathematical Problems in Engineering between system control (e.g., server quantity and waiting buffer) and user abandonment (e.g., reneging) on effective arrival rate and performances must all be taken into account. We discuss the problem of profit optimization in an abandonment system provided with finite capacity. (ii) The first presented optimal profit control (OPC) policy combined with a heuristic algorithm allows a cloud provider to effectively address constrained optimization problems. The effects of system capacities and utilizations on system performances and loss probabilities are demonstrated. (iii) Simulations show that the optimal decision making in server quantity and system capacity to maximize profit within a loss probability guarantee can be obtained by applying the proposed OPC policy.
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