Virtual Machine Scalability on Multi-Core Processors Based Servers for Cloud Computing Workloads

Jamal, Muhammad Hasan; Qadeer, Abdul; Mahmood, Waqar; Waheed, Abdul; Ding, Jiachen

doi:10.1109/nas.2009.20

Cited by 22 publications

(11 citation statements)

References 10 publications

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“…They showed how different resources scheduling and allocation strategies and workloads may impact the performance of a virtualized system. In [5] the authors proved that cache and memory architecture, network architecture and virtualization overheads can be scalability bottlenecks in a virtualized cloud, depending on whether the application is compute or memory or network I/O intensive respectively. None of these works proposed new techniques to improve I/O performance.…”

Section: Related Workmentioning

confidence: 99%

A dynamic bandwidth allocator for virtual machines in a cloud environment

Amamou

Bourguiba

Haddadou

et al. 2012

2012 IEEE Consumer Communications and Networking Conference (CCNC)

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Abstract-Cloud computing is an emergent paradigm that allows to customers to rent infrastructure, platforms and software as a service. With resource sharing and reuse through virtualization technology, cloud environments become even more effective and flexible. Nevertheless, networking within virtualized cloud still presents some challenges in performance and resource allocation. In this paper, we propose to integrate an SLA-based Dynamic Bandwidth Allocator (DBA) in a vitualized cloud environment. DBA manages bandwidth allocation efficiently through allocating bandwidth according to the application requirements and the established agreement. It also adjusts the allocated bandwidth dynamically upon change and reduces physical resources usage by dropping packets in the virtual machines rather than the driver domain. Through experimental evaluation we showed the efficacy of the proposed algorithm and the agreements respect.

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Section: Related Workmentioning

confidence: 99%

A dynamic bandwidth allocator for virtual machines in a cloud environment

Amamou

Bourguiba

Haddadou

et al. 2012

2012 IEEE Consumer Communications and Networking Conference (CCNC)

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“…However, by considering both pros and cons, we are convinced that the preferred configuration is the third one, since operating a completely virtualized environment, including even the OS, can provide a degree of flexibility in server usage and services deployment [19] that by far compensates the small performance degradation expected [27]. Instead, a common practice is a server consolidation through virtualization, which allows avoiding to run different and underutilized ASs in separated physical servers.…”

Section: A Application Server Deployment Configurationsmentioning

confidence: 99%

Performance management of Java-based SIP application servers

Femminella

Maccherani

Reali

2011

12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops

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Within the activities of the Java APIs for Integrated Networks (JAIN), the Java community offers a set of standard frameworks and open protocol APIs to create advanced telecommunications services. However, recent works have pointed out that Java-based implementations of the Session Initiation Protocol (SIP) stack, the fundamental signalling protocol in the convergent telephone-IP world, perform poorly if they are executed by large multi-core servers, typically used in data centres. The problem lies in the combination of the SIP protocol semantics with the Java language features, which does not allow fully exploiting the computing capabilities of multi-core architectures. To face this problem, we propose a solution to improve the throughput and signalling latency of applications implemented by using Java-based SIP application servers. It consists of the joint usage of virtualization and parallelization techniques. We have performed an extensive measurement campaign by using an open source application server compliant with the JSLEE (JAIN Service Logic Execution Environment) specifications. The rationale of this choice is that JSLEE application servers are currently regarded as very promising candidates for deploying telecom services. Results show that it is possible improving performance in terms of throughput and signalling latency by running more instances of the JSLEE server in parallel, each of them into separate virtual machines deployed on the same server. This improvement can increase throughput values of about 64% and, in the maximum throughput condition, the call set up latency can be nearly halved.

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“…As seen in this paper, the major contribution of performance overheads in a Cloud environment corresponds to machine virtualization. In this perspective, works that analyze the impact of virtualization in regard to CPU, memory, and network throughput are available 20, 21. The first work concluded that modern paravirtualization techniques available with Xen, imply very little overhead to both CPU and memory throughput.…”

Section: Related Workmentioning

confidence: 99%

“…As seen in this paper, the major contribution of performance overheads in a Cloud environment corresponds to machine virtualization. In this perspective, works that analyze the impact of virtualization in regard to CPU, memory, and network throughput are available [20,21] assigning each VM at least one physical core. They concluded that under those circumstances, and when communicating over the network, the overhead of separating several processes into the same amount of VMs is minimal when compared to using concurrent processes in an equivalent, non-virtualized host.…”

Section: Related Workmentioning

confidence: 99%

Performance and deployment evaluation of a parallel application on a private Cloud

Evoy

Schulze

Garcia

2011

Concurrency and Computation

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SUMMARYIn this paper we present the case study of an application of a parallel simulation optimization deployed on a private Cloud. The compute-intensive application uses a Master/Worker model, supporting communication over both Java RMI and Globus Grid Services between the nodes. The Master deploys Workers over a Eucalyptus Cloud using the Nimbus Context Broker for just-in-time configuration and runtime Worker discovery. The computational performance of the Workers under different communication mechanisms and deployment scenarios is presented in an attempt to evaluate the use of Virtual Machines in a Cloud as a tool to achieve application scaling. The deployment of this particular application was crafted to support on-the-fly addition of working nodes. The case study suggests a deployment pattern that shapes some requirements and considerations of a scalable Globus-driven Platform as a Service Cloud.

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Virtual Machine Scalability on Multi-Core Processors Based Servers for Cloud Computing Workloads

Cited by 22 publications

References 10 publications

A dynamic bandwidth allocator for virtual machines in a cloud environment

A dynamic bandwidth allocator for virtual machines in a cloud environment

Performance management of Java-based SIP application servers

Performance and deployment evaluation of a parallel application on a private Cloud

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