Xen2MX: High-performance communication in virtualized environments

Virtualization technologies are being actively used to design infrastructure of cloud computing systems. In this case applications can be duplicated and hosted in different virtual machines on different physical nodes. That defines various performance of applications which causes the problem of managing performance of the entire heterogeneous system. There are different ways of solving this problem, including queuing theory methods. However research of the threshold discipline in scope of queuing theory is not complete because of difficulty of gathering precise analytic values and building of precise mathematic model of the system. Another feature of heterogeneous systems is the finite random time of system functioning which is defined by random endogenous and exogenous factors. This paper gives an overview on a functional model of the system with two heterogeneous devices with random functioning time and different service disciplines. In scope of simulation statistic experiments for different service disciplines at random time interval an average time needed to process a single request is measured. A comparison of service disciplines is conducted. Authors also provide a working software implementation of the heterogeneous system and experiments with use of service disciplines is performed.

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“…The choice of Xen is motivated by its often usage in scheduling analyze and high-performance communications [12].…”

Section: Architecture Of the Software Environmentmentioning

confidence: 99%

Functional model of a software system with random time horizon

Zubok

Maiatin

Kiryushkina

et al. 2015

2015 17th Conference of Open Innovations Association (FRUCT)

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“…The communication between VMs on a single physical machine becomes very complex and frequent. Currently, since communication performance between different VMs on a single physical machine is affected by various aspects, the overhead can largely degrade communication performance [36,37,38]. Memory virtualization is one of the most common virtualization technologies, and the required user memory space may be much larger than the actual size of the machine’s memory.…”

Section: Introductionmentioning

confidence: 99%

Interdomain I/O Optimization in Virtualized Sensor Networks

Jiang

Fan

Qiu

et al. 2018

Sensors

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In virtualized sensor networks, virtual machines (VMs) share the same hardware for sensing service consolidation and saving power. For those VMs that reside in the same hardware, frequent interdomain data transfers are invoked for data analytics, and sensor collaboration and actuation. Traditional ways of interdomain communications are based on virtual network interfaces of bilateral VMs for data sending and receiving. Since these network communications use TCP/IP (Transmission Control Protocol/Internet Protocol) stacks, they result in lengthy communication paths and frequent kernel interactions, which deteriorate the I/O (Input/Output) performance of involved VMs. In this paper, we propose an optimized interdomain communication approach based on shared memory to improve the interdomain communication performance of multiple VMs residing in the same sensor hardware. In our approach, the sending data are shared in memory pages maintained by the hypervisor, and the data are not transferred through the virtual network interface via a TCP/IP stack. To avoid security trapping, the shared data are mapped in the user space of each VM involved in the communication, therefore reducing tedious system calls and frequent kernel context switches. In implementation, the shared memory is created by a customized shared-device kernel module that has bidirectional event channels between both communicating VMs. For performance optimization, we use state flags in a circular buffer to reduce wait-and-notify operations and system calls during communications. Experimental results show that our proposed approach can provide five times higher throughput and 2.5 times less latency than traditional TCP/IP communication via a virtual network interface.

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“…However, some challenges must be overcome to bridge the gap between performance provided by a dedicated infrastructure and the one supplied by clouds. Overheads introduced by virtualization layer, hardware heterogeneity and low latency networks, for example, affect negatively the performance of HPC applications when executed in clouds [4] [18] [38] [9] [31]. In addition, cloud providers usually adopt resource sharing policies that can worse even more HPC applications performances.…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Model for Predicting Cross-application Interference in Virtual Environments

Alves,

Drummond

2016

Preprint

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Cross-application interference can affect drastically performance of HPC applications when running in clouds. This problem is caused by concurrent access performed by co-located applications to shared and non-sliceable resources such as cache and memory. In order to address this issue, some works adopted a qualitative approach that does not take into account the amount of access to shared resources. In addition, a few works, even considering the amount of access, evaluated just the SLLC access contention as the root of this problem. However, our experiments revealed that interference is intrinsically related to the amount of simultaneous access to shared resources, besides showing that another shared resources, apart from SLLC, can also influence the interference suffered by co-located applications. In this paper, we present a quantitative model for predicting cross-application interference in virtual environments. Our proposed model takes into account the amount of simultaneous access to SLLC, DRAM and virtual network, and the similarity of application's access burden to predict the level of interference suffered by applications when colocated in a same physical machine. Experiments considering a real petroleum reservoir simulator and applications from HPCC benchmark showed that our model reached an average and maximum prediction errors around 4% and 12%, besides achieving an error less than 10% in approximately 96% of all tested cases.

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Xen2MX: High-performance communication in virtualized environments

Cited by 7 publications

References 29 publications

Functional model of a software system with random time horizon

Functional model of a software system with random time horizon

Interdomain I/O Optimization in Virtualized Sensor Networks

A Quantitative Model for Predicting Cross-application Interference in Virtual Environments

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