CloudNetSim++: A toolkit for data center simulations in OMNET++

Malik, Asad Waqar; Bilal, Kashif; Aziz, Khurram; Kliazovich, Dzmitry; Ghani, Nasir; Khan, Samee U.; Buyya, Rajkumar

doi:10.1109/honet.2014.7029371

Cited by 24 publications

(11 citation statements)

References 20 publications

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“…CloudNetSim++ [64] is a cloud simulator built upon OMNET ++. Like GreenCloud, this tool is focussed on power aware management techniques and energy consumption modelling.…”

Section: Cloudnetsim++mentioning

confidence: 99%

A Survey on Cloud Computing Simulation and Modeling

Bambrik

2020

SN COMPUT. SCI.

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Cloud Computing (CC) has attracted a massive amount of research and investment in the previous decade. The economical model proposed by this technology is a viable solution for consumers as well as being a profitable one for the provider. However, deploying real world cloud experiments to test new policies/algorithms is time consuming and very expensive, especially for large scenarios. As a result, the research community has opted to test their contributions is CC simulators. Although the models proposed by these simulators are not exhaustive, each one is made to address a specific process. Alternatively, others tools are made to provide a platform and the necessary building blocks to model any desired sub-component (application/ network model, energy consumption, scheduling and Virtual Machine provisioning). In this paper, a detailed survey about the existing CC simulators is made discussing features, software architecture as well as the ingenuity behind these frameworks.

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“…CloudNetSim++ [64] is a cloud simulator built upon OMNET ++. Like GreenCloud, this tool is focussed on power aware management techniques and energy consumption modelling.…”

Section: Cloudnetsim++mentioning

confidence: 99%

A Survey on Cloud Computing Simulation and Modeling

Bambrik

2020

SN COMPUT. SCI.

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“…Notably, the emulation environment helps to test the performance in a more realistic manner. Similarly, CloudNetSim++ is a packet‐level simulator designed for distributed data centers. It is implemented atop OMNeT++ using features of the INET framework.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another option, common among researchers and developers, is to use cloud simulators to benchmark the performance of test application under simulated cloud environment. Therefore, over the years a large number of cloud simulators and frameworks have been proposed; for instance, CloudSim, CloudNetSim++, iCanCloud, and many more are discussed later in the literature review.…”

Section: Introductionmentioning

confidence: 99%

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Toward scalable cloud data center simulation using high‐level architecture

et al. 2019

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Existing simulators are designed to simulate a few thousand nodes due to the tight integration of modules. Thus, with limited simulator scalability, researchers/developers are unable to simulate protocols and algorithms in detail, although cloud simulators provide geographically distributed data centers environment but lack the support for execution on distributed systems.In this paper, we propose a distributed simulation framework referred to as CloudSimScale. The framework is designed on top of highly adapted CloudSim with communication among different modules managed using IEEE Std 1516 (high-level architecture). The underlying modules can now run on the same or different physical systems and still manage to discover and communicate with one another. Thus, the proposed framework provides scalability across distributed systems and interoperability across modules and simulators. KEYWORDSbroker, cloud computing, CloudSim, distributed simulation, HLA, RTI INTRODUCTIONCloud data centers provide services in the form of infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS). With flexible resource provisioning model on back-end data centers, it allows users to deploy applications from anywhere using dynamically allocated resources as per requirements in the service-level agreement. The most well-known cloud service providers are Amazon EC2 * , Microsoft Azure † , Google cloud ‡ , and IBM § with emerging cloud-based applications like content delivery, navigation systems, social networks, and many more.Evidently, the main contribution of cloud computing is the provision of a dynamic virtual environment that scales transparently to support a large number of users concurrently. This comes with provisioning of cloud services in pay-as-you-go-model, while the cloud providers are responsible for ensuring the quality of services. In general, it is difficult Abbreviations: IaaS, infrastructure-as-a-service; HLA, high-level architecture; RTI, runtime infrastructure; LRC, local RTI components; CRC, central RTI component; CIS, cloud information service.Recent contributions in cloud simulation environment mainly focus on scheduling algorithms, VM migrations, software-defined networking-based networking, and energy efficiency. However, there is limited work toward scalability of existing simulators. Most of them at most support simulation with a few thousands of nodes. Due to this limitation, researchers often find it difficult to simulate realistic data center models. In this paper, we have proposed CloudSim-Scale based on CloudSim to provide access to a scalable environment for researchers. The framework decouples existing CloudSim modules so that they can be independently placed on different systems. Thus, to support the resulting intercommunication among the modules, a separate layer of HLA-RTI is implemented. Furthermore, CloudSimScale allows the integration of various simulators to facilitate researchers in simulating complex scenarios. For instance, internet of things (IoT)/edge s...

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“…In [6] the authors have presented a very detailed model of a data center architecture which is analyzed through simulations. However the assumptions about the traffic are rather simple.…”

Section: Introductionmentioning

confidence: 99%

A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption

Bayati¹,

Dahmoune²,

Fourneau³

et al. 2016

Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools

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We present a tool to study the trade-off between energy consumption and performance evaluation. The tool uses real traffic traces to model arrivals, and it allows to consider general discrete arrival processes. Some servers are switched on (resp. off) if the monitored QoS becomes less (resp. more) than the up (resp. down) threshold. A set of threshold couples and the cost function taking into account both the performance measure and the energy consumption are provided by the user. The tool determines the best one for this cost function among the analyzed scenarios. Our method is numerically based but it takes into account some stochastic properties of the model to speed up the computation.

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CloudNetSim++: A toolkit for data center simulations in OMNET++

Cited by 24 publications

References 20 publications

A Survey on Cloud Computing Simulation and Modeling

A Survey on Cloud Computing Simulation and Modeling

Toward scalable cloud data center simulation using high‐level architecture

A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption

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