Improving cloud architectures using UML profiles and M2T transformation techniques

Bernal, Adrián; Cambronero, M. Emilia; Núñez, Alberto; Cañizares, Pablo C.; Valero, Valentín

doi:10.1007/s11227-019-02980-w

Cited by 15 publications

(18 citation statements)

References 35 publications

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“… Performance Evaluation. Once the model has been validated, the configuration files are generated for the cloud simulator (Simcan2Cloud ( Bernal et al, 2019a )). Simulations are then executed, providing us with the performance metrics, namely the number of regular / high-priority users that were served, the number of them that left the system without being served, the waiting times for the users, etc.…”

Section: Methodsmentioning

confidence: 99%

“…Hence, the modeling tool has been extended as well, so that we can easily create and edit parameterized cloud models, so as to consider different cloud infrastructures and different pricing schemes. In addition, these UML models can be validated, and then we can generate the input configuration files required to carry out the performance evaluation using the Simcan2Cloud simulator ( Bernal et al, 2019a ).…”

Section: Motivation and Contributionmentioning

confidence: 99%

“…The workloads are generated using, as their basis, two different user roles: regular users and high-priority users. The experiments in this study were run on the Simcan2Cloud simulator ( Bernal et al, 2019a ). In summary, the process for carrying out the experiments consists of the following steps: (1) modeling five cloud environments using MSCC; (2) generating the configuration files representing these clouds for the Simcan2Cloud simulator; (3) encoding the behavior of the users represented in “CloudCost Profile” into Simcan2Cloud; and (4) simulating the processing of each workload in the five cloud environments modeled.…”

Section: Case Studymentioning

confidence: 99%

“…The proposed UML profile captures the main elements of the cloud infrastructure and the client interactions, which is reflected in a methodological way to model different scenarios and then launch the corresponding simulations on a cloud simulator. As testbed, we use the simulator Simcan2Cloud ( Bernal et al, 2019a ), which makes it possible to load the cloud scenarios created by the (Modeling SLAs Cost Cloud) tool and simulate the execution of the workloads generated, which consist of a large number of users. It is worth noting that these simulations can be executed on a personal computer, and therefore no special features are required of the platform to support these executions.…”

Section: Introductionmentioning

confidence: 99%

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Profiling SLAs for cloud system infrastructures and user interactions

Cambronero

Bernal

Valero

et al. 2021

PeerJ Computer Science

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Cloud computing has emerged as a cutting-edge technology which is widely used by both private and public institutions, since it eliminates the capital expense of buying, maintaining, and setting up both hardware and software. Clients pay for the services they use, under the so-called Service Level Agreements (SLAs), which are the contracts that establish the terms and costs of the services. In this paper, we propose the CloudCost UML profile, which allows the modeling of cloud architectures and the users’ behavior when they interact with the cloud to request resources. We then investigate how to increase the profits of cloud infrastructures by using price schemes. For this purpose, we distinguish between two types of users in the SLAs: regular and high-priority users. Regular users do not require a continuous service, so they can wait to be attended to. In contrast, high-priority users require a constant and immediate service, so they pay a greater price for their services. In addition, a computer-aided design tool, called MSCC (Modeling SLAs Cost Cloud), has been implemented to support the CloudCost profile, which enables the creation of specific cloud scenarios, as well as their edition and validation. Finally, we present a complete case study to illustrate the applicability of the CloudCost profile, thus making it possible to draw conclusions about how to increase the profits of the cloud infrastructures studied by adjusting the different cloud parameters and the resource configuration.

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Section: Methodsmentioning

confidence: 99%

Section: Motivation and Contributionmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Profiling SLAs for cloud system infrastructures and user interactions

Cambronero

Bernal

Valero

et al. 2021

PeerJ Computer Science

Self Cite

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“…In addition, modeling the cloud infrastructure and the users' interactions with the cloud providers allow us to have a better understanding of the behavior of all the roles in these systems. With this purpose in mind, we defined the UML2Cloud profile [1]. The main features of the cloud infrastructure, that is, CPUs, storage, and network bandwidth, among others, are considered in this parameterized profile, as well as the exchange of messages between the users and the cloud provider, with parameters such as the specification of the virtual machines required, the applications to be executed on them, and the maximum subscription time when the requested machines are not available at the time of the request.…”

Section: Introductionmentioning

confidence: 99%

Studying the Impact of the User Subscription Times in Different Cloud Configurations

De¹

2021

Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering

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In this paper, we model cloud systems and the user interactions with the cloud provider using the UML2Cloud profile. In general, users request virtual machines according to their needs, but they can also subscribe to the cloud provider and wait to be notified when the requested resources are not available. In this case, users indicate a maximum subscription time, so once this time elapses without being notified, users leave the system unattended. In this paper, then, we present an exhaustive research study to measure how the user subscription times affect the overall system responsiveness. In this study, three different cloud configurations are analyzed. Each cloud processes several workloads, which are generated using two distribution functions for the user arrivals, namely a normal and a cyclic normal distribution. The purpose of this study is to find out the inflection point for the waiting time of the users, from which the cloud responsiveness and its performance do not improve. The obtained information is therefore useful for the cloud provider to improve the configuration of the cloud.

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Model Based HSI & Operational Process Simulation

Peleg

Gavish

Zonnenshain³

2022

INCOSE International Symp

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Human‐Systems Integration (HSI) activities are focused on the human engineering aspects of the systems designing, manufacturing, operation, and maintenance. It is part of the system engineering process. Model‐Based Systems Engineering (MBSE) is a concept, which is implemented by languages and software tools, for supporting all activities of development, operation, and system retirement, using a set of coherent models. This paper proposed how MBSE usage can be used to support the holistic HSI, from requirements and operational analysis, through retirement. The suggested methodology, which includes the use of Operational Process (OP) diagrams and model‐based 3D (three dimensional) simulation, can be applied to introduce further discipline and rigor to address complex HSI, marking an improvement over current document‐based practice.

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Improving cloud architectures using UML profiles and M2T transformation techniques

Cited by 15 publications

References 35 publications

Profiling SLAs for cloud system infrastructures and user interactions

Profiling SLAs for cloud system infrastructures and user interactions

Studying the Impact of the User Subscription Times in Different Cloud Configurations

Model Based HSI & Operational Process Simulation

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