Parallel processors provide fast computing environments for various users.But the real efficiencies ofparallel processors intensively depend on the partitioning strategies of tasks over the processors.In thispaper,the...Parallel processors provide fast computing environments for various users.But the real efficiencies ofparallel processors intensively depend on the partitioning strategies of tasks over the processors.In thispaper,the partitioning problems of independent tasks for homogeneous system of parallel processors arequantitatively studied.We adopt two criteria,minimizing the completion time and the total waiting time,to determine the optimal partitioning strategy.展开更多
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
基金This work was supported in part by the National Natural Science Foundation of China and in part by the 863 Project.
文摘Parallel processors provide fast computing environments for various users.But the real efficiencies ofparallel processors intensively depend on the partitioning strategies of tasks over the processors.In thispaper,the partitioning problems of independent tasks for homogeneous system of parallel processors arequantitatively studied.We adopt two criteria,minimizing the completion time and the total waiting time,to determine the optimal partitioning strategy.
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.
