How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data cente...How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.展开更多
Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic info...Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.展开更多
Science data are very important resources for innovative research in all scientific disciplines. The Ministry of Science and Technology （MOST） of China has launched a comprehensive platform program for supporting sc...Science data are very important resources for innovative research in all scientific disciplines. The Ministry of Science and Technology （MOST） of China has launched a comprehensive platform program for supporting scientific innovations and agricultural science database construction and sharing project is one of the activities under this program supported by MOST. This paper briefly described the achievements of the Agricultural Science Data Center Project.展开更多
Cloud computing is becoming a key factor in the market day by day. Therefore, many companies are investing or going to invest in this sector for development of large data centers. These data centers not only consume m...Cloud computing is becoming a key factor in the market day by day. Therefore, many companies are investing or going to invest in this sector for development of large data centers. These data centers not only consume more energy but also produce greenhouse gases. Because of large amount of power consumption, data center providers go for different types of power generator to increase the profit margin which indirectly affects the environment. Several studies are carried out to reduce the power consumption of a data center. One of the techniques to reduce power consumption is virtualization. After several studies, it is stated that hardware plays a very important role. As the load increases, the power consumption of the CPU is also increased. Therefore, by extending the study of virtualization to reduce the power consumption, a hardware-based algorithm for virtual machine provisioning in a private cloud can significantly improve the performance by considering hardware as one of the important factors.展开更多
In modern data centers, because of the deadline- agnostic congestion control in transmission control protocol （TCP）, many deadline-sensitive flows can not finish before their deadlines. Therefore, providing a higher...In modern data centers, because of the deadline- agnostic congestion control in transmission control protocol （TCP）, many deadline-sensitive flows can not finish before their deadlines. Therefore, providing a higher deadline meeting ratio becomes a critical challenge in the typical online data intensive （OLDI） ap- plications of data center networks （DCNs）. However, a problem named as priority synchronization is found in this paper, which de- creases the deadline meeting ratio badly. To solve this problem, we propose a priority probability deceleration （P2D） deadline-aware TCP. By using the novel probabilistic deceleration, p2D prevents the priority synchronization problem. Simulation results show that P2D increases the deadline meeting ratio by 20% compared with D2TCP.展开更多
基金supported by the National Natural Science Foundation of China(6120200461272084)+9 种基金the National Key Basic Research Program of China(973 Program)(2011CB302903)the Specialized Research Fund for the Doctoral Program of Higher Education(2009322312000120113223110003)the China Postdoctoral Science Foundation Funded Project(2011M5000952012T50514)the Natural Science Foundation of Jiangsu Province(BK2011754BK2009426)the Jiangsu Postdoctoral Science Foundation Funded Project(1102103C)the Natural Science Fund of Higher Education of Jiangsu Province(12KJB520007)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(yx002001)
文摘How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.
基金supported by the National Postdoctoral Science Foundation of China(2014M550068)
文摘Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.
基金Supported by Ministry of Science and Technology"National Science and Technology Platform Program"(2005DKA31800)
文摘Science data are very important resources for innovative research in all scientific disciplines. The Ministry of Science and Technology （MOST） of China has launched a comprehensive platform program for supporting scientific innovations and agricultural science database construction and sharing project is one of the activities under this program supported by MOST. This paper briefly described the achievements of the Agricultural Science Data Center Project.
基金supported by the National Research Foundation (NRF) of Korea through contract N-14-NMIR06
文摘Cloud computing is becoming a key factor in the market day by day. Therefore, many companies are investing or going to invest in this sector for development of large data centers. These data centers not only consume more energy but also produce greenhouse gases. Because of large amount of power consumption, data center providers go for different types of power generator to increase the profit margin which indirectly affects the environment. Several studies are carried out to reduce the power consumption of a data center. One of the techniques to reduce power consumption is virtualization. After several studies, it is stated that hardware plays a very important role. As the load increases, the power consumption of the CPU is also increased. Therefore, by extending the study of virtualization to reduce the power consumption, a hardware-based algorithm for virtual machine provisioning in a private cloud can significantly improve the performance by considering hardware as one of the important factors.
基金supported by the National Natural Science Foundation of China(611630606110320461462007)
文摘In modern data centers, because of the deadline- agnostic congestion control in transmission control protocol （TCP）, many deadline-sensitive flows can not finish before their deadlines. Therefore, providing a higher deadline meeting ratio becomes a critical challenge in the typical online data intensive （OLDI） ap- plications of data center networks （DCNs）. However, a problem named as priority synchronization is found in this paper, which de- creases the deadline meeting ratio badly. To solve this problem, we propose a priority probability deceleration （P2D） deadline-aware TCP. By using the novel probabilistic deceleration, p2D prevents the priority synchronization problem. Simulation results show that P2D increases the deadline meeting ratio by 20% compared with D2TCP.
