Refining Service Delay Using Temporal Task Scheduling for Profit Maximization in Hybrid Cloud
Elankavi R, Dr. Udayakumar R
Heuristic Algorithm, Hybrid Clouds, Profit Maximization, Service Delay, Task Scheduling.
As cloud computing is becoming growingly popular, consumers’ tasks around the world arrive in cloud data centers. A private cloud provider aims to achieve profit maximization by intelligently scheduling tasks while guaranteeing the service delay bound of delay-tolerant tasks. However, the aperiodicity of arrival tasks brings a challenging problem of how to dynamically schedule all arrival tasks given the fact that the capacity of a private cloud provider is limited. Previous works usually provide an admission control to intelligently refuse some of arrival tasks. Nevertheless, this will decrease the throughput of a private cloud, and cause revenue loss. This paper studies the problem of how to maximize the profit of a private cloud in hybrid clouds while guaranteeing the service delay bound of delay-tolerant tasks. We propose a profit maximization algorithm (PMA) to discover the temporal variation of prices in hybrid clouds. The temporal task scheduling provided by PMA can dynamically schedule all arrival tasks to execute in private and public clouds. The sub problem in each iteration of PMA is solved by the proposed hybrid heuristic optimization algorithm, simulated annealing particles warm optimization (SAPSO). Besides, SAPSO is compared with existing baseline algorithms. Extensive simulation experiments demonstrate that the proposed method can greatly increase the throughput and the profit of a private cloud while guaranteeing the service delay bound. Note to Practitioners: This paper aims to solve the problem of task scheduling for a private cloud in hybrid clouds. The aperiodicity of arrival tasks brings a challenge of maximizing the profit of a private cloud provider while guaranteeing the service delay bound of delay-tolerant tasks. Existing methods usually provide an admission control to refuse some of arrival tasks that exceed the capacity of a private cloud. This paper first proposes an architecture of temporal task scheduling in hybrid clouds. Based on the architecture, a PMA algorithm is proposed to provide temporal task scheduling which can maximize the profit of a private cloud by intelligently dispatching arrival tasks to execute in private and public clouds within the service delay bound. Preliminary simulation experiments show that the proposed temporal task scheduling is feasible but it has not yet been implemented in real hybrid clouds. In future research, we will extend this work to incorporate multiple different tasks that require heterogeneous resources including bandwidth.