With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and im...With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and improve the efficiency of data center has become the research focus of researchers all the world. In a cloud environment, virtual machine consolidation(VMC) is an effective strategy that can improve the energy efficiency. However, at the same time, in the process of virtual machine consolidation, we need to deal with the tradeoff between energy consumption and excellent service performance to meet service level agreement(SLA). In this paper, we propose a new virtual machine consolidation framework for achieving better energy efficiency-Improved Underloaded Decision(IUD) algorithm and Minimum Average Utilization Difference(MAUD) algorithm. Finally, based on real workload data on Planet Lab, experiments have been done with the cloud simulation platform Cloud Sim. The experimental result shows that the proposed algorithm can reduce the energy consumption and SLA violation of data centers compared with existing algorithms, improving the energy efficiency of data centers.展开更多
In cloud computing data centers,containerized tasks are regularly scheduled from one physical host to another due to resource management requirements such as handling machine failures,rebalancing server resources,and ...In cloud computing data centers,containerized tasks are regularly scheduled from one physical host to another due to resource management requirements such as handling machine failures,rebalancing server resources,and upgrading/scaling applications.After the container running in the source host is scheduled to the target host,it suffers from I/O performance degradation until the DRAM buffer is fully rebuilt.However,migrating the DRAM buffer from the source host to the target host could also introduce intolerable downtime of containerized tasks.Especially,as the DRAM buffer capacity of the application already increases to about dozens or hundreds of GB,the cost of downtime due to container migration becomes unacceptable.Many researchers have devoted themselves to developing an effective DRAM buffer warm-up scheme to avoid the cold bootstrap issue after container migration,such as pre-copy and post-copy schemes.However,the cold bootstrap and large-capacity buffer migration issues of container scheduling are still an open research problem.In this paper,motivated by the observation that the DRAM buffer is always flushed to the storage backend before starting the container in the target host,we proposed a scheme named ZeroCopy to utilize the file system to assist the DRAM buffer migration.ZeroCopy traverses the files in the DRAM buffer and flags these files when these files are flushed into the file system,and reloads these files into DRAM after starting the container in the target host.By this scheme,the container migration procedure does not require migrating data buffers and can start within an acceptable time.We conduct a series of experiments with public cloud traces to measure several key metrics on container migration.The results show that ZeroCopy outperforms these existing schemes.The average data transmission volume is reduced by about 6.25 times compared with state-of-the-art,and the downtime of container migration is also reduced by 31.8%.展开更多
基金supported by the National Natural Science Foundation of China (NSFC) (No. 61272200, 10805019)the Program for Excellent Young Teachers in Higher Education of Guangdong, China (No. Yq2013012)+2 种基金the Fundamental Research Funds for the Central Universities (2015ZJ010)the Special Support Program of Guangdong Province (201528004)the Pearl River Science & Technology Star Project (201610010046)
文摘With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and improve the efficiency of data center has become the research focus of researchers all the world. In a cloud environment, virtual machine consolidation(VMC) is an effective strategy that can improve the energy efficiency. However, at the same time, in the process of virtual machine consolidation, we need to deal with the tradeoff between energy consumption and excellent service performance to meet service level agreement(SLA). In this paper, we propose a new virtual machine consolidation framework for achieving better energy efficiency-Improved Underloaded Decision(IUD) algorithm and Minimum Average Utilization Difference(MAUD) algorithm. Finally, based on real workload data on Planet Lab, experiments have been done with the cloud simulation platform Cloud Sim. The experimental result shows that the proposed algorithm can reduce the energy consumption and SLA violation of data centers compared with existing algorithms, improving the energy efficiency of data centers.
基金supported by the National Natural Science Foundation of China under Grant No.62202368.
文摘In cloud computing data centers,containerized tasks are regularly scheduled from one physical host to another due to resource management requirements such as handling machine failures,rebalancing server resources,and upgrading/scaling applications.After the container running in the source host is scheduled to the target host,it suffers from I/O performance degradation until the DRAM buffer is fully rebuilt.However,migrating the DRAM buffer from the source host to the target host could also introduce intolerable downtime of containerized tasks.Especially,as the DRAM buffer capacity of the application already increases to about dozens or hundreds of GB,the cost of downtime due to container migration becomes unacceptable.Many researchers have devoted themselves to developing an effective DRAM buffer warm-up scheme to avoid the cold bootstrap issue after container migration,such as pre-copy and post-copy schemes.However,the cold bootstrap and large-capacity buffer migration issues of container scheduling are still an open research problem.In this paper,motivated by the observation that the DRAM buffer is always flushed to the storage backend before starting the container in the target host,we proposed a scheme named ZeroCopy to utilize the file system to assist the DRAM buffer migration.ZeroCopy traverses the files in the DRAM buffer and flags these files when these files are flushed into the file system,and reloads these files into DRAM after starting the container in the target host.By this scheme,the container migration procedure does not require migrating data buffers and can start within an acceptable time.We conduct a series of experiments with public cloud traces to measure several key metrics on container migration.The results show that ZeroCopy outperforms these existing schemes.The average data transmission volume is reduced by about 6.25 times compared with state-of-the-art,and the downtime of container migration is also reduced by 31.8%.
