CloudNetSim++: A GUI Based Framework for Modeling and Simulation of Data Centers in OMNeT++

Malik, Asad Waqar; Bilal, Kashif; Malik, Saif Ur Rehman; Anwar, Zahid; Aziz, Khurram; Kliazovich, Dzmitry; Ghani, Nasir; Khan, Samee U.; Buyya, Rajkumar

doi:10.1109/tsc.2015.2496164

Cited by 19 publications

(9 citation statements)

References 34 publications

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“…For example, Li et al [17] proposed DartCSIM to enable the simulation of energy and network simultaneously. Other Cloud simulators have been proposed, like iCanCloud [18], but they are not designed to support distributed DC architectures [19]. Malik et al [19] proposed CloudN etSim++ which is a GUI-Based framework for modeling and simulation of DCs in OMNeT++ including simulation models for network devices.…”

Section: B Energy Models and Simulation Toolsmentioning

confidence: 99%

Estimating Energy Consumption of Cloud, Fog, and Edge Computing Infrastructures

Ahvar

Orgerie

Lèbre

2022

IEEE Trans. Sustain. Comput.

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In order to improve locality aspects, new Cloudrelated architectures such as Edge Computing have been proposed. Despite the growing popularity of these new architectures, their energy consumption has not been well investigated yet. To move forward on such a critical question, we first introduce a taxonomy of different Cloud-related architectures. From this taxonomy, we then present an energy model to evaluate their consumption. Unlike previous proposals, our model comprises the full energy consumption of the computing facilities, including cooling systems, and the energy consumption of network devices linking end users to Cloud resources. Finally, we instantiate our model on different Cloud-related architectures, ranging from fully centralized to completely distributed ones, and compare their energy consumption. The results show that a completely distributed architecture, because of not using intra-data center network and large-size cooling systems, consumes between 14% and 25% less energy than fully centralized and partly distributed architectures respectively. To the best of our knowledge, our work is the first one to propose a model that enables researchers to analyze and compare energy consumption of different Cloudrelated architectures.

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Section: B Energy Models and Simulation Toolsmentioning

confidence: 99%

Estimating Energy Consumption of Cloud, Fog, and Edge Computing Infrastructures

Ahvar

Orgerie

Lèbre

2022

IEEE Trans. Sustain. Comput.

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“…OMNeT++ framework has matured since its inception in 1997 with frequent releases 5 . In addition to the maturity, and widespread use among the scientific community [33] [34], OMNeT++ enabled the development of a modular, component based toolkit to simulate the inherent characteristics of edge-cloud streaming applications and networks.…”

Section: Ecsnet++ Simulation Toolkitmentioning

confidence: 99%

“…We gained inspiration from the CPU module and the scheduling policies introduced in this work, when developing our computation model. Similarly, CloudNetSim++ [34], which focuses on the aspects of cloud computing, is also built on top of OMNeT++. Table 1 compares our proposed solution against other relevant state-of-theart modelling and simulation tools available in the literature.…”

Section: Related Workmentioning

confidence: 99%

ECSNeT++ : A simulator for distributed stream processing on edge and cloud environments

Amarasinghe

Assunção

Harwood

et al. 2020

Future Generation Computer Systems

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The objective of Internet of Things (IoT) is ubiquitous computing. As a result many computing enabled, connected devices are deployed in various environments, where these devices keep generating unbounded event streams related to the deployed environment. The common paradigm is to process these event streams at the cloud using the available Distributed Stream Processing (DSP) frameworks. However, with the emergence of Edge Computing, another convenient computing paradigm has been presented for executing such applications. Edge computing introduces the concept of using the underutilised potential of a large number of computing enabled connected devices such as IoT, located outside the cloud. In order to develop optimal strategies to utilise this vast number of potential resources, a realistic test bed is required. However, due to the overwhelming scale and heterogeneity of the edge computing device deployments, the amount of effort and investment required to set up such an environment is high. Therefore, a realistic simulation environment that can accurately predict the behaviour and performance of a large-scale, real deployment is extremely valuable. While the state-of-the-art simulation tools consider different aspects of executing applications on edge or cloud computing environments, we found that no simulator considers all the key characteristics to perform a realistic simulation of the execution of DSP applications on edge and cloud computing environments. To the best of our knowledge, the publicly available simulators lack being verified against real world experimental measurements, i.e. for calibration and to obtain accurate estimates of e.g. latency and power consumption. In this paper, we present our ECSNeT++ simulation toolkit which has been verified using real world experimental measurements for executing DSP applications on edge and cloud computing environments. ECSNeT++ models deployment and processing of DSP applications on edge-cloud environments and is built on top of OMNeT++/INET. By using multiple configurations of two real DSP applications, we show that ECSNeT++ is able to model a real deployment, with proper calibration. We believe that with the public availability of ECSNeT++ as an open source framework, and the verified accuracy of our results, ECSNeT++ can be used effectively for predicting the behaviour and performance of DSP applications running on large scale, heterogeneous edge and cloud computing device deployments.

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“…Experimental simulations in OMNeT++ have proven to be a reliable approach for supporting studies in large-scale networks [46] that are not hardware dependent and therefore easy to scale and analyze. The role of experimental simulations using the OMNeT++ network simulator is quite significant in the performance evaluation of novel mechanisms in scientific literature [47]. In our study, it enables us to research the behavior and performance of the proposed eTDP in many realistic scenarios of geographically distributed realworld networks.…”

Section: A Simulation Environmentmentioning

confidence: 99%

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

2019

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Discovering network elements in a dynamic and optimized manner and being able to contend with ever-growing traffic is a key requirement for current networking environments. In software-defined networks (SDNs), the controller collects the topology information from the data plane and maintains an abstract view of the entire network, which is crucial for the proper functioning of applications and network services. However, there is still the need for an enhanced protocol for automatic discovery and mechanisms of autoconfiguration of network elements according to new policies and business requirements. To overcome this challenge, this paper presents a novel protocol that, unlike existing approaches, enables a distributed layer-2 discovery without the need for previous network configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. The obtained results show that our enhanced protocol is efficient in terms of time and message load over a wide range of generated networks and outperforms the state-of-the-art techniques. INDEX TERMS Network management, protocols, software-defined networks, topology discovery. CRISTINA CERVELLÓ-PASTOR received the M.Sc. and Ph.D. degrees in telecommunication engineering from the Barcelona School of Telecommunications Engineering, Politècnica de Catalunya, Barcelona, Spain, where she is currently an Associate Professor and the Head of the Department of Network Engineering. Being part of the BAMPLA Research Group, she is responsible and actively participated in diverse national and European competitive projects (NOVI, FEDER-ICA, ATDMA, A@DAN, Euro-NGI, Euro-FGI, and EURONF) and private funding research and development projects. She has published diverse papers in national and international journals and conferences. She is supervising dissertation in the field of management, optimal resource allocation, topology discovery, and routing in software-defined networks/NFV and 5G.

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CloudNetSim++: A GUI Based Framework for Modeling and Simulation of Data Centers in OMNeT++

Cited by 19 publications

References 34 publications

Estimating Energy Consumption of Cloud, Fog, and Edge Computing Infrastructures

Estimating Energy Consumption of Cloud, Fog, and Edge Computing Infrastructures

ECSNeT++ : A simulator for distributed stream processing on edge and cloud environments

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

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