Comparative study of simulators for cloud computing

Maarouf, Adil; Marzouk, Abderrahim; Haqiq, Abdelkrim

doi:10.1109/cloudtech.2015.7336989

Cited by 10 publications

(4 citation statements)

References 17 publications

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“…CloudSim proposed in 2009 [46]. CloudSim's multifaceted [27] software [67] framework scheme and structural components are shown in Figure 5.…”

Section: A Cloudsim Architecturementioning

confidence: 99%

A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm

Shahid¹,

Faiz²,

Alam³

et al. 2022

JISR-C

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Cloud computing (CC) provides fast and on-demand access to virtually unlimited computing resources. Mobile cloud computing (MCC) is a new technology that brings CC and mobile devices together. MCC allows mobile devices access to cloud services. Describe the basic architectures for various MCC applications, as well as a brief comparison of cloud and MCC. As CC becomes more common, researchers in this field may need to conduct real-world experiments in their studies. Configuring and running these experiments in real-world cloud environments is costly. As a consequence, modeling and simulation approaches are suitable solutions that can be used to simulate cloud computing environments. Several simulation tools tailored to CC have been developed. The most powerful simulation methods in this field of study are described in this article. Among them are CloudSim, CloudSim Plus, CloudAnalyst, iFogSim, and CloudReports.

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“…CloudSim proposed in 2009 [46]. CloudSim's multifaceted [27] software [67] framework scheme and structural components are shown in Figure 5.…”

Section: A Cloudsim Architecturementioning

confidence: 99%

A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm

Shahid¹,

Faiz²,

Alam³

et al. 2022

JISR-C

View full text Add to dashboard Cite

show abstract

“…The cloud's highly dynamic nature also makes testing methods difficult to repeat [55]. A literature review was conducted to identify a suitable model [56] [57]. Those design parameters are addressed below.…”

Section: Experiments Designmentioning

confidence: 99%

Cloud Security Game Theory Scoring From Predation Models In Simulation

Alsup

Putluru

Cui

et al. 2022

Preprint

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Cloud economics results from amassing computation resources while being able to distribute workload in space and time. The backbone of this ability is virtualization, which abstracts the host hardware, sharing virtual machines. This means of interface is also a primary vehicle and target for attackers. The counter-measures to this threat consider the costs and benefits to the cloud’s essential functions. Where the future development of the cloud is also considered, this competition between attackers and victims is analogous to those modeled in extended game theory. Yet, the attacker and victim costs and benefits, expressed as utility measures necessary for game-theory methods, are elusive quantities. This paper establishes such a game as a predator-prey contest played out on a data-center environment. A set of contestant parameters are applied at the threshold of a viable model to the recognizable boundaries. Measurement of system health is extracted in relief with individual cost, benefit, and risk. An examination of metrics capable of validating extended interaction is developed. This establishes a baseline model for more elaborate expression of security in cloud economics.

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“…There are different simulators that have been developed to perform experimentation in cloud environments. CloudSim [4] is one of the most popular [1,37] and sophisticated [20] cloud simulation tool. It is a discrete event simulator implemented in Java that can be extended to incorporate new features.…”

Section: Cloud Simulatorsmentioning

confidence: 99%

CloudBench: an integrated evaluation of VM placement algorithms in clouds

et al. 2020

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A complex and important task in the cloud resource management is the efficient allocation of virtual machines (VMs), or containers, in physical machines (PMs). The evaluation of VM placement techniques in real-world clouds can be tedious, complex, and time-consuming. This situation has motivated an increasing use of cloud simulators that facilitate this type of evaluations. However, most of the reported VM placement techniques based on simulations have been evaluated considering one specific cloud resource (e.g., CPU), whereas values often unrealistic are assumed for other resources (e.g., RAM, awaiting times, application workloads, etc.). This situation generates uncertainty, discouraging their implementations in real-world clouds. This paper introduces CloudBench, a methodology to facilitate the evaluation and deployment of VM placement strategies in private clouds. CloudBench considers the integration of a cloud simulator with a real-world private cloud. Two main tools were developed to support this methodology, a specialized multiresource cloud simulator (CloudBalanSim), which oversees evaluating VM placement techniques, and a distributed resource manager (Balancer), which deploys and tests in a real-world private cloud the best VM placement configurations that satisfied user requirements defined in the simulator. Both tools generate feedback information, from the evaluation scenarios and their obtained results, which is used as a learning asset to carry out intelligent and faster evaluations. The experiments implemented with the CloudBench methodology showed encouraging results as a new strategy to evaluate and deploy VM placement algorithms in the cloud. Keywords Load balancing • Cloud simulator • Cloud resource management • IntroductionCloud computing is a paradigm in which computing resources, such as computing units, storage, servers, applications, etc., are offered as an on-

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Comparative study of simulators for cloud computing

Cited by 10 publications

References 17 publications

A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm

A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm

Cloud Security Game Theory Scoring From Predation Models In Simulation

CloudBench: an integrated evaluation of VM placement algorithms in clouds

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