vPipe: piped i/o offloading for efficient data movement in virtualized clouds

Virtualization introduces a significant amount of overhead for I/O intensive applications running inside virtual ma-chines (VMs). Such overhead is caused by two main sources: (1) device virtualization and (2) VM scheduling. Device virtualization causes significant CPU overhead as I/O data need to be moved across several protection boundaries. VM scheduling introduces delays to the overall I/O processing path due to the wait time of VMs ’ virtual CPUs in the run queue. We observe that such overhead particularly affects many applications involving piped I/O data movements, such as web servers, streaming servers, big data analytics, and storage, because the data has to be transferred first into the application from the source I/O device and then back to the sink I/O device, incurring the virtualization overhead twice. In this paper, we propose vPipe, a programmable framework to mitigate this problem for a wide range of applications running in virtualized clouds. vPipe enables direct “piping” of application I/O data from source to sink devices, either files or TCP sockets, at virtual machine monitor (VMM) level. By doing so, vPipe can avoid both device virtualiza-tion overhead and VM scheduling delays, resulting in im-proved I/O throughput and application performance as well as significant CPU savings