A Service Revenue-oriented Task Scheduling Model of Cloud Computing

摘要

Task scheduling strategy aims at finding an effective matching method between computing resources and submitted tasks, so as to achieve the reasonable allocation and effective execution of a large number of submitted tasks among computing resources. As a commercial service, cloud computing should gain as much service revenue as possible on condition that the QoS requirements of submitted tasks are satisfied. However, the majority of the existing cloud task scheduling methods aim at meeting the resource requests and QoS constraints of submitted tasks rather than earning more service revenue. Focusing on this point, a service revenue-oriented task scheduling model of cloud computing is proposed in this paper, which tries to improve the service revenue of cloud providers under the same condition. The final experimental results demonstrate that the service revenue-oriented cloud task scheduling strategy is superior to the classic Min-min algorithm and the improved Min-min algorithm based on QoS constraints in terms of the scheduling makespan of all submitted tasks and the service revenue per unit computing cost of the whole cloud system.