| With rapid development of cloud computing,most applications are deployed or migrated to cloud data centers.These applications bring huge challenge to quality of service(QoS)in data centers,due to the requirements of each application are different.The continuous innovation of technology makes the development of task scheduling method more perfect.As a result,customers have high pursuit on QoS of data centers.In order to satisfy customers'requirements,there is more resource should be deployed in cloud data center and lead to sharp increase in energy consumption.So,how to balance energy consumption against QoS has already been a hot issue.This paper studies on QoS-Based Energy-Aware task scheduling method;aiming at meeting customers' QoS requirements while reducing energy consumption.The major work is as follows:(1)For the problem of high energy consumption and cost in data centers,this paper proposed a QoS-Enhanced Green resource scheduling policy.First,the relationship between energy and cost and an energy consumption model are presented.While scheduling tasks,tasks should be divided into different groups and the state of physical machines(PM)should be taken into account.In order to reduce the number of running PMs and running time,appropriate state switching operation should be proposed base on certain threshold.Finally,experimental analysis is conducted to evaluate the effectiveness of the proposed policy.(2)It is still a challenge to achieve energy savings based on QoS during task scheduling.In this part,a QoS-based energy-aware task scheduling method,named QET,in cloud environment is proposed to address the above challenge.Technically,an energy consumption model based on QoS is proposed for heterogeneous cloud environment.And a corresponding task scheduling method is designed to minimize the energy consumption through QoS-aware PM selection.Comprehensive experimental analysis is conducted to evaluate the efficiency and effectiveness of the presented policy. |
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