Speed and Accuracy of Network Simulation in the SimGrid Framework

Fujiwara, Kayo; Casanova, Henri

doi:10.4108/nstools.2007.2010

Cited by 30 publications

(35 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• We reproduce and confirm the results of [11] but using a more precise and well-suited error model. We also use a more unified and justified protocol running more experiments than what was previously done.…”

Section: Introductionsupporting

confidence: 76%

“…One such framework, SimGrid, uses a flow-level approach that approximates the behavior of TCP networks, including TCP's bandwidth sharing properties. A preliminary study of the accuracy loss by comparing it to popular packet-level simulators has been proposed in [11] and in which regimes in which SimGrid's accuracy is comparable to that of these packet-level simulators are identified. In this article we come back on this study, reproduce these experiments and provide a deeper analysis that enables us to greatly improve SimGrid's range of validity.…”

Section: Introductionmentioning

confidence: 99%

“…• We propose a finer analysis than the one proposed in [11] and we study more precisely the validity range of the SimGrid model.…”

Section: Introductionmentioning

confidence: 99%

“…Fujiwaraet al [11] have proposed a preliminary study of the accuracy of the SimGrid model comparing obtained results with packet-level simulations and have highlighted non-neglectable flaws. In this article, we come back on their study and improve on their results by making a finer analysis that enables us to propose a more accurate model at very low cost.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Accuracy study and improvement of network simulation in the SimGrid framework

Velho¹,

Legrand²

2009

Proceedings of the Second International ICST Conference on Simulation Tools and Techniques

View full text Add to dashboard Cite

Distributed computing is a very broad and active research area comprising fields such as cluster computing, computational grids, desktop grids and peer-to-peer (P2P) systems. Studies in this area generally resort to simulations, which enable reproducible results and make it possible to explore wide ranges of platform and application scenarios. In this context, network simulation is certainly the most critical part. Many packet-level network simulators are available and enable high-accuracy simulation but they lead to prohibitively long simulation times. Therefore, many simulation frameworks have been developed that simulate networks at higher levels, thus enabling fast simulation but losing accuracy. One such framework, SimGrid, uses a flow-level approach that approximates the behavior of TCP networks, including TCP's bandwidth sharing properties. A preliminary study of the accuracy loss by comparing it to popular packet-level simulators has been proposed in [11] and in which regimes in which SimGrid's accuracy is comparable to that of these packet-level simulators are identified. In this article we come back on this study, reproduce these experiments and provide a deeper analysis that enables us to greatly improve SimGrid's range of validity.

show abstract

Section: Introductionsupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

“…• We propose a finer analysis than the one proposed in [11] and we study more precisely the validity range of the SimGrid model.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Accuracy study and improvement of network simulation in the SimGrid framework

Velho¹,

Legrand²

2009

Proceedings of the Second International ICST Conference on Simulation Tools and Techniques

View full text Add to dashboard Cite

show abstract

“…For Grids, another set of simulators have been developed, such as GridSim [3], OptorSim [1], SimGrid [13] and MicroGrid [19], among others. These tools can simulate brokerage of resources, or execution of different types of applications on different types of computing resources, but as before they lack the details to simulate a cloud environment.…”

Section: Introductionmentioning

confidence: 99%

iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

et al. 2012

View full text Add to dashboard Cite

Simulation techniques have become a powerful tool for deciding the best starting conditions on pay-as-you-go scenarios. This is the case of public cloud infrastructures, where a given number and type of virtual machines (in short VMs) are instantiated during a specified time, being this reflected in the final budget. With this in mind, this paper introduces and validates iCanCloud, a novel simulator of cloud infrastruc-tures with remarkable features such as flexibility, scalability, performance and usability. Further-more, the iCanCloud simulator has been built on the following design principles: (1) it's targeted to conduct large experiments, as opposed to oth-ers simulators from literature; (2) it provides a flexible and fully customizable global hypervisor for integrating any cloud brokering policy; (3) it reproduces the instance types provided by a given cloud infrastructure; and finally, (4) it contains a user-friendly GUI for configuring and launching simulations, that goes from a single VM to large cloud computing systems composed of thousands of machines.Keywords Cloud computing · Cloud computing simulator · Cloud hypervisor · Validation · Scalability 1 to solve a given computational problem. If the same software and configurations are needed, the VMs may be started using the same image. This way, a machine offered by a computing cloud may become whatever the user needs, from a standalone computer to a cluster or Grid node.Nowadays, cloud computing systems are increasing their role due to the fast (r)evolution of computer networks and communication technologies. A very clear proof of this fact is that very important companies like Amazon, Google, Dell, IBM, and Microsoft are investing billions of dollars in order to provide their own cloud solutions [28].As soon as the scientific community had access to cloud production infrastructures, the first applications started to run on the cloud [26,34]. In many Research areas, the leap from traditional cluster and Grid computing to this new paradigm has been mandatory, being the main reason an evolution in the computational needs of the applications [10]. A remarkable fact from this evolution is that in a pre-cloud environment, hardware defines the level of parallelism of an application. In cloud computing, the level of parallelism is defined by the application itself, as there is no restriction in the number of machines, and CPU availability is 100% guaranteed by standard.There

show abstract

A toolkit for modelling and simulating data Grids: an extension to GridSim

Sulistio

Cibej

Venugopal

et al. 2008

Concurrency and Computation

132

View full text Add to dashboard Cite

SUMMARYData Grids are an emerging technology for managing large amounts of distributed data. This technology is highly anticipated by scientific communities, such as in the area of astronomy and high-energy physics, because their experiments generate massive amounts of data which need to be shared and analysed. Since it is not feasible to test different usages on real testbeds, it is easier to use simulations as a means of studying complex scenarios. This paper presents our work on incorporating data Grids features as an extension to GridSim, a computational Grid simulator. The extension provides essential building blocks for simulating various data Grids scenarios. Moreover, it is designed to be easily extended. This approach makes it easy to try various strategies and to add functionalities to suit the needs of other communities. This paper also gives a detailed description of the design and usage examples demonstrating the versatility of this tool.

show abstract

Speed and Accuracy of Network Simulation in the SimGrid Framework

Cited by 30 publications

References 23 publications

Accuracy study and improvement of network simulation in the SimGrid framework

Accuracy study and improvement of network simulation in the SimGrid framework

iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

A toolkit for modelling and simulating data Grids: an extension to GridSim

Contact Info

Product

Resources

About