Building an automated and self‐configurable emulation testbed for grid applications

Calheiros, Rodrigo N.; Buyya, Rajkumar; Rose, César A. F. De

doi:10.1002/spe.964

Cited by 20 publications

(16 citation statements)

References 21 publications

(32 reference statements)

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“…EMUSIM [95] builds on top of CLOUDSIM by adding an emulation step leveraging the Automated Emulation Framework (AEF) [96]. Emulation is used to understand the application behavior, extracting profiling information.…”

Section: Simulation Modelsmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

211

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Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. This paper aims at supporting research in this area by providing a survey of the state of the art of QoS modeling approaches suitable for cloud systems. We also review and classify their early application to some decision-making problems arising in cloud QoS management.

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Section: Simulation Modelsmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

211

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“…In the case of CloudSim [4], several research articles have been published with results obtained by using it [2,5,6,15]. This tool was initially based on a Grid simulator [4] (this being GridSim [27]).…”

Section: Introductionmentioning

confidence: 99%

iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

et al. 2012

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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

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“…There are several research articles, in the case of CloudSim, which focus the obtained results on this simulator [2,4,10]. This tool was initially based on a grid simulator [3] (this being GridSim [16]).…”

Section: Motivationmentioning

confidence: 99%

A methodology for validating cloud models using metamorphic testing

Núñez

Hierons

2014

Ann. Telecommun.

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Cloud computing is a paradigm that provides access to a flexible, elastic and on-demand computing infrastructure, allowing users to dynamically request virtual resources. However, researchers typically cannot experiment with critical parts of cloud systems such as the underlying cloud architecture, resource-provisioning policies and the configuration of resource virtualisation. This problem can be partially addressed through using simulations of cloud systems. Unfortunately, the problem of testing cloud systems is still challenging due to the many parameters that such systems typically have and the difficulty in determining whether an observed behaviour is correct. In order to alleviate these issues, we propose a methodology to semi-automatically test and validate cloud models by integrating simulation techniques and metamorphic testing.

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Building an automated and self‐configurable emulation testbed for grid applications

Cited by 20 publications

References 21 publications

Quality-of-service in cloud computing: modeling techniques and their applications

Quality-of-service in cloud computing: modeling techniques and their applications

iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

A methodology for validating cloud models using metamorphic testing

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