High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await i...High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.展开更多
Due to the increasing sizes of cloud data centers, the number of virtual machines （VMs） and applications rises quickly. The rapid growth of large scale Internet services re- suits in unbalanced load of network resou...Due to the increasing sizes of cloud data centers, the number of virtual machines （VMs） and applications rises quickly. The rapid growth of large scale Internet services re- suits in unbalanced load of network resource. The bandwidth utilization rate of some physical hosts is too high, and this causes network congestion. This paper presents a layered VM migration algorithm （LVMM）. At first, the algorithm will divide the cloud data center into several regions according to the bandwidth utilization rate of the hosts. Then we bal- ance the load of network resource of each region by VM migrations, and ultimately achieve the load balance of net- work resource in the cloud data center. Through simulation experiments in different environments, it is proved that the LVMM algorithm can effectively balance the load of network resource in cloud computing.展开更多
基金supported by Research and Innovation Projects for Graduates of Jiangsu Graduates of Jiangsu Province (No. CXZZ12 0483)the Science and Technology Support Program of Jiangsu Province (No. BE2012849)
文摘High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.
文摘Due to the increasing sizes of cloud data centers, the number of virtual machines （VMs） and applications rises quickly. The rapid growth of large scale Internet services re- suits in unbalanced load of network resource. The bandwidth utilization rate of some physical hosts is too high, and this causes network congestion. This paper presents a layered VM migration algorithm （LVMM）. At first, the algorithm will divide the cloud data center into several regions according to the bandwidth utilization rate of the hosts. Then we bal- ance the load of network resource of each region by VM migrations, and ultimately achieve the load balance of net- work resource in the cloud data center. Through simulation experiments in different environments, it is proved that the LVMM algorithm can effectively balance the load of network resource in cloud computing.
