Who Is Your Neighbor: Net I/O Performance Interference in Virtualized Clouds

Abstract

Abstract-User-perceived performance continues to be the most important QoS indicator in cloud-based data centers today. Effective allocation of virtual machines (VMs) to handle both CPU intensive and I/O intensive workloads is a crucial performance management capability in virtualized clouds. Although a fair amount of researches have dedicated to measuring and scheduling jobs among VMs, there still lacks of in-depth understanding of performance factors that impact the efficiency and effectiveness of resource multiplexing and scheduling among VMs. In this paper, we present the experimental research on performance interference in parallel processing of CPU-intensive and network-intensive workloads on Xen virtual machine monitor (VMM). Based on our study, we conclude with five key findings which are critical for effective performance management and tuning in virtualized clouds. First, colocating network-intensive workloads in isolated VMs incurs high overheads of switches and events in Dom0 and VMM. Second, colocating CPU-intensive workloads in isolated VMs incurs high CPU contention due to fast I/O processing in I/O channel. Third, running CPU-intensive and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. Fourth, performance of network-intensive workload is insensitive to CPU assignment among VMs, whereas adaptive CPU assignment among VMs is critical to CPU-intensive workload. The more CPUs pinned on Dom0 the worse performance is achieved by CPU-intensive workload. Last, due to fast I/O processing in I/O channel, limitation on grant table is a potential bottleneck in Xen. We argue that identifying the factors that impact the total demand of exchanged memory pages is important to the in-depth understanding of interference costs in Dom0 and VMM.

Billing the CPU Time Used by System Components on Behalf of VMs

“…Several works have investigated I/O virtualization issue [20], [19], [11], [16], [18]. Nonetheless, several studies [7], [15] have highlighted performance unpredictability in the cloud because of the VMs competition on shared resources. Works in this field can be classified in two categories.…”

“…A VM is launched with a fixed allocated computing capacity that should be strictly provided by the hosting system scheduler. The respect of the allocated capacity has two main motivations: (1) For the customer, performance isolation and predictability [7], [15], i.e. a VM performance should not be influenced by other VMs running on the same physical machine.…”

Server Consolidation for Internet Applications in Virtualized Data Centers

“…We design two applications by the benchmark, abk and abm. They transmit a fixed size file: 1KB, 1MB, which are representative log sizes in current data center [43], to their requests, respectively. Additional, to reduce the disk readings for increasing the performance, files are cached in the buffers in advance.…”

Billing system CPU time on individual VM

“…The underlying hosting system (hypervisor) schedules VMs and ensures that the allocated CPU capacity is provided and respected. The respect of the allocated capacity has two main motivations: (1) For the customer, performance isolation and predictability [8], [9], i.e. a VM performance should not be influenced by other VMs running on the same physical machine.…”