<p>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&#xa0;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%.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

ZeroCopy: file system assisted container buffer migration in cloud computing system

  • Shiqiang Nie,
  • Tingshen Ruan,
  • Ruijia Chen,
  • Bo Song,
  • Song Liu,
  • Weiguo Wu

摘要

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%.