A Comparative Analysis of Cloud Simulators

Pericherla, Suryateja Satya

doi:10.5815/ijmecs.2016.04.08

Cited by 26 publications

(13 citation statements)

References 20 publications

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“…On the other hand, the authors tend to use simulation tools in their experimental work which presents 84%. This is due to the high cost and difficulty of implementation caused by the evaluation in a real environment (see Figure 3.a) [57].…”

Section: Simulation Tools Comparisonmentioning

confidence: 99%

“…Most of the simulations (56%) are carried out using a Simulator Toolkit (see Figure 3.b), because these tools facilitate the development, modeling and evaluation of the model to be simulated by using the functionalities offered by the Toolkit. This allows the researchers to focus on the simulation and analysis of the proposed approach's behavior, analyze the results obtained in the various simulation scenarios [57,58], and not focus on the details of programming the model to be simulated.…”

Section: Simulation Tools Comparisonmentioning

confidence: 99%

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A Survey on Various Methods and Algorithms of Scheduling in Fog Computing

Belmahdi¹,

Mechta²,

Harous³

2021

ISI

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The rapid deployment of IoT in different areas generates a massive amount of data transferred to the Cloud. To solve this challenge a new paradigm, called Fog Computing, is located at the edge of the network and close to the connected objects. Its main role is to extend the capacities of Cloud and improve the performance and the QoS required by the applications by the use of different methods and techniques based on scheduling algorithms. In this paper, we review various recent studies available in the literature that are interested in the scheduling methods and algorithms used in Fog computing. The use of fog layer, in solving optimization problem, is faced with serious challenges. Therefore, to help practitioners and researchers, we present an in-depth overview of Fog Computing studying various scheduling methods and algorithms. We analyze, compare and classify these different scheduling approaches according to the nature of the algorithm used in the scheduling, the QoS optimized by the proposed approach and the type of applications in order to show what is suitable for critical IoT (CIOT), massive IoT (MIOT) and Industry IoT (IIOT). Finally, we present a comparison of the different simulation tools used to evaluate these approaches to guide fog computing developers/researchers which tool is suitable and most flexible for simulating the application under consideration.

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Section: Simulation Tools Comparisonmentioning

confidence: 99%

Section: Simulation Tools Comparisonmentioning

confidence: 99%

A Survey on Various Methods and Algorithms of Scheduling in Fog Computing

Belmahdi¹,

Mechta²,

Harous³

2021

ISI

View full text Add to dashboard Cite

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“…as well as communication between the packet levels. Further, it offers to know the workload distribution in the system [24,25]. These simulators have to be taken for comparative study because these are specifically designed for the measurement of energy consumption in cloud computing environments.…”

Section: Related Workmentioning

confidence: 99%

A Comparative Study between Cloud Energy Consumption Measuring Simulators

Hassaan¹

2020

IJEME

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Cloud computing is the study of using remote servers which are hosted on the internet to deliver on-demand computing resources on pay-for-use basis rather than a local server. Due to high energy consumption in cloud computing environments, it has become the main area of research. The amount of energy consumption becomes difficult to determine in real cloud computing infrastructure. In recent years some simulation tools have been developed to analyze the energy consumption in cloud computing environments for the researchers. This paper evaluates three different popular cloud energy consumption measuring simulators: CloudSim, CloudAnalyst and GreenCloud. All of these simulators can determine energy consumption according to their ability and capacity. The comparative study indicates that in a cloud computing environment, GreenCloud simulator is better than CloudSim and CloudAnalyst due to reliable measurement of energy consumption. The significance of this comparative study is to help out the researchers who are working on energy consumption in cloud computing environments that how GreenCloud simulator make their work efficient rather than other simulators.

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“…The user has no control or managing rights over the underlying cloud infrastructure i.e. storage, operating systems, networks or servers but only have the control over the deployed applications [43]. Google app engine is one of the examples.…”

Section: Platform As a Service (Paas)mentioning

confidence: 99%

Cloud Computing: A Paradigm Shift in the Way of Computing

Agarwal¹,

Srivastava²

2017

IJMECS

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Cloud computing has been emerging out as a new and evolving paradigm with tremendous momentum. It is one of the most acceptable information technology based service which drew the attention of the people not only from the academia, industry but also registered its popularity among the general people. Features like scalability, elasticity, less entry cost, easy to access and subscription and pay per use etc. compel the businesses and end users to migrate themselves from the traditional platform to the cloud based platform. With the wide acceptability of cloud computing based services in the society, people have various myths like some think it as a new name of internet, as it shares many features of the internet while others feel it as another name of existing technology like distributed system, grid computing, and parallel computing etc.. This paper will help in making people aware of this technology by highlighting the points of difference with the existing technology and focusing on the various advantages and area of application which presents the evidence of its popularity and continual growth. The work in the paper will end with the discussion on the status of various issues and shortcomings from which it is suffering along with the present and future scope in this popular area.

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A Comparative Analysis of Cloud Simulators

Cited by 26 publications

References 20 publications

A Survey on Various Methods and Algorithms of Scheduling in Fog Computing

A Survey on Various Methods and Algorithms of Scheduling in Fog Computing

A Comparative Study between Cloud Energy Consumption Measuring Simulators

Cloud Computing: A Paradigm Shift in the Way of Computing

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