vCPU as a container: towards accurate CPU allocation for VMs

Liu, Li; Wang, Dan; Wang, An; Xiao, Mengbai; Cheng, Yue; Chen, Songqing

doi:10.1145/3313808.3313814

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…A prototype I-Balancer was designed and developed based on the Xen 4.12 based para-virtualized system, and Table 3 outlines the overall experimental environment and configuration. For the resource configuration of the VM, vCPUs were pinned to a total of two pCPUs with pCPU0-1 for the six vCPUs allocated to DOM0 to avoid performance interference caused by the pCPU preemption contention and four vCPUs allocated to all guest VMs, and the remaining vCPUs were pinned to pCPU2-7 [5], [15], [40], [47], [48]. All vCPUs can perform vCPU migration for load-balancing against a pinned pCPU pool.…”

Section: Methodsmentioning

confidence: 99%

Fine-Grained I/O Traffic Control Middleware for I/O Fairness in Virtualized System

Lee

2022

IEEE Access

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The development of IT technology in the 21st century has created a new paradigm for real-time, data-intensive user services, such as connected cars, smart factories, and remote health care services. The considerable computational resources required by these services are rendering the cloud increasingly more important. In the cloud server, user services are forced to share physical resources because of the emerging resource competition, thus introducing various types of unpredictable workloads. The core technology of the cloud is a virtualized system, which isolates and shares the powerful physical resources of the server in the form of a virtual machine (VM) to increase resource efficiency. However, the scheduling policy of a virtual CPU (vCPU), which is a logical CPU of a VM, generally schedules the vCPU based on the degree of occupation of the physical CPU (pCPU) without regarding I/O strength; so it brings the unfair I/O performance among VMs in the virtualized systems. The user services performing on the VM are not aware of the user-contention architectures, which sharing of I/O devices, in the virtualized systems; Furthermore, the current virtualized system simply adopts the Linux-based I/O processing process which optimized for user-contention-free architectures. Therefore, the architecture that brings the unfair usage of I/O devices among user services is hardly regarded and has low awareness in current virtualized systems. To overcome this problem, in this study, I-Balancer is presented to provide fair I/O performance among I/O-intensive user services by applying an asynchronous inter-communication control technique for the virtualized system with a high VM density. The main design goal of I-Balancer is to increase the awareness of user-contention architectures in the hypervisor. I-Balancer derives the fine-grained workload and I/O strength for each vCPU during the scheduler and event channel areas. Subsequently, to strengthen fair I/O performance, an I/O traffic control mechanism is implemented to control the inter-domain communication traffic according to the I/O strength of the VMs. The experimental results prove that I-Balancer provides a fairer network and disk I/O performance than the existing virtualized systems with negligible performance interference and overhead.

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Section: Methodsmentioning

confidence: 99%

Fine-Grained I/O Traffic Control Middleware for I/O Fairness in Virtualized System

Lee

2022

IEEE Access

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“…For example, when a server is not overloaded, I/O operations may be offloaded to redundant cores, not slowing down the workloads in the VMs. We argue that this 'concealed' cost is important for 2 reasons: firstly, public cloud environments are evolving towards charging consumers for CPU cycles used by their VMs [34], rather than VM uptime (e.g. serverless environments [35]).…”

Section: Defining Virtualization Overheadmentioning

confidence: 99%

Virtualization Overhead of Multithreading in X86 State-of-the-Art & Remaining Challenges

Schildermans

Shan

Aerts

et al. 2021

IEEE Trans. Parallel Distrib. Syst.

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Despite great advancements in hardware-assisted virtualization of the x86 architecture, certain workloads still suffer significant overhead. This work dissects said overhead in the context of multi-threading. We describe the state of the art, pinpoint challenges and suggest improvements, aiming to provide a valuable reference to developers and users of virtualization systems alike. We study the virtualization overhead of the PARSEC and SPLASH2X multithreaded benchmarks in a variety of scenarios using a state-of-the-art system. Through controlled experiments, source code analysis and literature review, we quantify the virtualization overhead multithreading still induces and link it to its root causes, after which we suggest possible mitigation strategies. Multithreading still induces high virtualization overhead, mainly caused by synchronization, spinning at user level and NUMA management. The overhead is diverse in nature and embodiment as it is a function of many system and workload properties. System-level solutions are feasible, but often imply difficult trade-offs. Systematic workload optimization is a promising alternative.

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“…In this case, in a virtualization environment with limited resources, the workload type of the vCPU must be recognized and a scheduling policy that can adapt to the workload type of the vCPU must be devised. Some authors insist that the degradation of I/O performance in a virtualized environment emerges when DOM0, also known as the driver domain, is scheduled with the guest VM on the same core [17,[24][25][26]. More specifically, because DOM0 handles I/O requests from all guest VMs, the vCPUs of DOM0 that handle the VM's I/O requests cannot guarantee pCPU preoccupation by the vCPUs of the guest VM.…”

Section: Motivationmentioning

confidence: 99%

“…Xen has adopted a split-driver model that comprises a driver domain (DOM0) and a user's VM (guest VM). DOM0 has a physical driver that handles the I/O of the guest VMs [9,13,[16][17][18]. The guest VM has a logical driver that sends an I/O request to the backend driver of DOM0 when an I/O appears.…”

Section: Introductionmentioning

confidence: 99%

I/O Strength-Aware Credit Scheduler for Virtualized Environments

Lee

2020

Electronics

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With the evolution of cloud technology, the number of user applications is increasing, and computational workloads are becoming increasingly diverse and unpredictable. However, cloud data centers still exhibit a low I/O performance because of the scheduling policies employed, which are based on the degree of physical CPU (pCPU) occupancy. Notably, existing scheduling policies cannot guarantee good I/O performance because of the uncertainty of the extent of I/O occurrence and the lack of fine-grained workload classification. To overcome these limitations, we propose ISACS, an I/O strength-aware credit scheduler for virtualized environments. Based on the Credit2 scheduler, ISACS provides a fine-grained workload-aware scheduling technique to mitigate I/O performance degradation in virtualized environments. Further, ISACS uses the event channel mechanism in the virtualization architecture to expand the scope of the scheduling information area and measures the I/O strength of each virtual CPU (vCPU) in the run-queue. Then, ISACS allocates two types of virtual credits for all vCPUs in the run-queue to increase I/O performance and concurrently prevent CPU performance degradation. Finally, through I/O load balancing, ISACS prevents I/O-intensive vCPUs from becoming concentrated on specific cores. Our experiments show that compared with existing virtualization environments, ISACS provides a higher I/O performance with a negligible impact on CPU performance.

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vCPU as a container: towards accurate CPU allocation for VMs

Cited by 7 publications

References 18 publications

Fine-Grained I/O Traffic Control Middleware for I/O Fairness in Virtualized System

Fine-Grained I/O Traffic Control Middleware for I/O Fairness in Virtualized System

Virtualization Overhead of Multithreading in X86 State-of-the-Art & Remaining Challenges

I/O Strength-Aware Credit Scheduler for Virtualized Environments

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