Eli

Gordon, Abel; Amit, Nadav; Har'El, Nadav; Ben-Yehuda, Muli; Landau, Alex; Schuster, Assaf; Tsafrir, Dan

doi:10.1145/2150976.2151020

Cited by 126 publications

(2 citation statements)

References 25 publications

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“…They also studied the effect of allocated resource to VMs and found that pinning more cores for Dom0 results in low performance of CPU-bound workloads. It is due to the fact that Dom0, which maintains driver Domain, mediates and performs more I/O operations than other domains in Xen hypervisor [34]. They found that the higher the workload rate or the larger the request size, the higher the CPU overhead incurred in Dom0.…”

Section: Introductionmentioning

confidence: 99%

“…They found that the higher the workload rate or the larger the request size, the higher the CPU overhead incurred in Dom0. It is due to the fact that Dom0, which maintains driver Domain, mediates and performs more I/O operations than other domains in Xen hypervisor [34] Numerous studies have attempted to model the performance of virtualized systems by using queuing theory. Menascé used analytical modeling to evaluate the performance of virtualized systems and quantify the effect of VM consolidation on the slowdown of the application's performance [25].…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of Web server workloads in Xen‐based virtualized computer system: analytical modeling and experimental validation

RahimiZadeh

Gerde

Analoui

et al. 2015

Concurrency and Computation

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Recent developments in the field of virtualization technologies have led to renewed interest in performance evaluation of these systems. Nowadays, maturity of virtualization technology has made a fuss of provisioning IT services to maximize profits, scalability and QoS. This pioneer solution facilitates deployment of datacenter applications and grid and Cloud computing services; however, there are challenges. It is necessary to investigate a trade-off among overall system performance and revenue and to ensure service-level agreement of submitted workloads. Although a growing body of literature has investigated virtualization overhead and virtual machines interference, there is still lack of accurate performance evaluation of virtualized systems. In this paper, we present in-depth performance measurements to evaluate a Xen-based virtualized Web server. Regarding this experimental study; we support our approach by queuing network modeling. Based on these quantitative and qualitative analyses, we present the results that are important for performance evaluation of consolidated workloads on Xen hypervisor. First, demands of both CPU intensive and disk intensive workloads on CPU and disk are independent from the submitted rate to unprivileged domain when dedicated core(s) are pinned to virtual machines. Second, request response time not only depends on processing time at unprivileged domain but also pertains to amount of flipped pages at Domain 0. Finally, results show that the proposed modeling methodology performs well to predict the QoS parameters in both para-virtualized and hardware virtual machine modes by knowing the request content size. Copyright resources among multiple VMs to run in an isolated operational environment. VMM mediates issued requests from VMs, conveys them to the physical resources, and provides an appropriate environment in which VMs can coexist. In fact, the VMM layer provides an isomorphism to map VMs behaviors including states and operation sequences to the host machine.Despite all of the server virtualization benefits, it faces challenges. To begin with, VMM only virtualizes operating systems (OSs), and consolidated applications are not aware of running on the virtualized environment. Although the hypervisor mediates VMs to access resources, running applications might face performance degradation due to their operational interferences [2][3][4]. On the other hand, interference among VMs may lead to more performance degradation. It conflicts with the virtualization claim to provide an isolated operational environment. Secondly, none of the current virtualization technologies are singlehandedly appropriate to all applications. In this way, designated appropriate hypervisor, OS and resource assignment schemes regarding each workload type are important. Resource configuration directly affects hypervisor performance, which, consequently, permutes the quality of service (QoS) of submitted workloads [5,6].Thirdly, despite security and fault concerns of consolidation of VMs, workloads with high r...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance evaluation of Web server workloads in Xen‐based virtualized computer system: analytical modeling and experimental validation

RahimiZadeh

Gerde

Analoui

et al. 2015

Concurrency and Computation

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Seamless integration of cloud and fog networks

Cardoso

Barraca

Goncalves³

et al. 2016

Int J Network Mgmt

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Summary A way to merge cloud computing infrastructures with traditional or legacy network deployments, leveraging the best in both worlds and enabling a logically centralized control. A solution is proposed to extend existing cloud computing software stacks so they are able to manage networks outside the cloud computing infrastructure, the fog, by extending the internal, virtualized network segments. This is useful in a variety of use cases such as incremental legacy to cloud network migration, hybrid virtual/traditional networking, centralized control of existing networks, bare metal provisioning, and even offloading of advanced services from typical home gateways into the operator. Any organization can develop different ‘drivers’ to support new, specific networking equipment, not necessarily tied to a protocol or vendor, and leverage the fog network. Our conceptual solution is prototyped on top of OpenStack, including changes to the API, command‐line interface (CLI), and other mechanisms. Test results indicate that there are low penalties on latency and throughput, and provisioning times are reduced in comparison with similar maintenance operations on traditional computer networks. Copyright © 2016 John Wiley & Sons, Ltd.

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The Uber eXtensible Micro-Hypervisor Framework (uberXMHF)

Vasudevan

2019

Practical Security Properties on Commodity Computing Platforms

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Eli

Cited by 126 publications

References 25 publications

Performance evaluation of Web server workloads in Xen‐based virtualized computer system: analytical modeling and experimental validation

Performance evaluation of Web server workloads in Xen‐based virtualized computer system: analytical modeling and experimental validation

Seamless integration of cloud and fog networks

The Uber eXtensible Micro-Hypervisor Framework (uberXMHF)

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