Software techniques to improve virtualized I/O performance on multi-core systems

Abstract

Virtualization technology is now widely deployed on high performance networks such as 10-Gigabit Ethernet (10GE). It offers useful features like functional isolation, manageability and live migration. Unfortunately, the overhead of network I/O virtualization significantly degrades the performance of network-intensive applications. Two major factors of loss in I/O performance result from the extra driver domain to process I/O requests and the extra scheduler inside the virtual machine monitor (VMM) for scheduling domains.In this paper we first examine the negative effect of virtualization in multi-core platforms with 10GE networking. We study virtualization overhead and develop two optimizations for the VMM scheduler to improve I/O performance. The first solution uses cache-aware scheduling to reduce inter-domain communication cost. The second solution steals scheduler credits to favor I/O VCPUs in the driver domain. We also propose two optimizations to improve packet processing in the driver domain. First we re-design a simple bridge for more efficient switching of packets. Second we develop a patch to make transmit (TX) queue length in the driver domain configurable and adaptable to 10GE networks. Using all the above techniques, our experiments show that virtualized I/O bandwidth can be increased by 96%. Our optimizations also improve the efficiency by saving 36% in core utilization per gigabit. All the optimizations are based on pure software approaches and do not hinder live migration. We believe that the findings from our study will be useful to guide future VMM development.

A New Task Scheduling Algorithm using Firefly and Simulated Annealing Algorithms in Cloud Computing

“…Liao [11] presented a scheduler for scheduling real time applications for supporting respond time, and instead of placing the processor at the end of the executive queue, this method compute the state in which the virtual processor is inserted based on its delay. Goiri [12] presented a task dynamic scheduling policy for allocating informed sources at cloud data centers.…”

A Queuing based Network I/O Scheduling with QoS Guarantee for Virtual Machine

“…Memory and cache also affect I/O performance. Guangdeng Liao et al, [7] proposed a cache-aware scheduling and credits steal strategy to improve I/O performance. Their mechanism reduces inter-domain communication cost and accelerates packet processing.…”

“…Several techniques have been proposed for improving I/O performance [6][7][8][9]. Software based [6][7][8] and hardware based [9] I/O virtualization technology are applied in virtualization to improve network I/O performance.…”

“…Software based [6][7][8] and hardware based [9] I/O virtualization technology are applied in virtualization to improve network I/O performance. Such I/O technologies are advantageous in high performance computing, and cloud computing environment, where I/O is a major performance bottleneck.…”

Providing Performance Guarantees to Virtual Machines Using Real-Time Scheduling

“…In [17], the authors proposed an extension to the Xen credit-based scheduler improving its behavior in presence of multiple different applications with heavy I/O workloads, prioritizing the I/O bound ones. Also, in [13], the authors proposed to modify the Xen CPU scheduler and networking architecture to improve the performance of virtualized I/O on 10 Gbps Ethernet.…”