Improving cloud architectures using UML profiles and M2T transformation techniques

In this paper, we present an approach with the goal to improve the underlying architecture of cloud systems. For this, we propose UML2Cloud, a framework targeted at modeling and checking cloud systems. The main core of UML2Cloud uses UML profiles to capture the main elements of a cloud system including, among other elements, its underlying architecture and the interaction with clients. Additionally, UML2Cloud uses Model-to-Text transformation techniques to automatically generate configuration documents representing complex cloud scenarios. In this work, we use these documents as input for a cloud simulation tool, called Simcan2Cloud, to simulate the behavior of different systems. Thus, the analysis of the performance results obtained from the simulations allows us to draw some conclusions about how to improve the efficiency of the studied clouds by adjusting the hardware resource configuration.

[1]  C. K. Filelis-Papadopoulos,et al.  A framework for simulating large scale cloud infrastructures , 2018, Future Gener. Comput. Syst..

[2]  Thomas C. Schmidt,et al.  An extension of the OMNeT++ INET framework for simulating real-time ethernet with high accuracy , 2011, SimuTools.

[3]  Xiao Zhang,et al.  DriftInsight: Detecting Anomalous Behaviors in Large-Scale Cloud Platform , 2017, 2017 IEEE 10th International Conference on Cloud Computing (CLOUD).

[4]  Oliver Kopp,et al.  TOSCA: Portable Automated Deployment and Management of Cloud Applications , 2014, Advanced Web Services.

[5]  Reinhard German,et al.  SYNTONY: network protocol simulation based on standard-conform UML 2 models , 2007, ValueTools '07.

[6]  Mohammad S. Obaidat,et al.  An adaptive task allocation technique for green cloud computing , 2017, The Journal of Supercomputing.

[7]  Jesús Carretero,et al.  SIMCAN: A flexible, scalable and expandable simulation platform for modelling and simulating distributed architectures and applications , 2012, Simul. Model. Pract. Theory.

[8]  Frank Leymann,et al.  Moving Applications to the Cloud: an Approach Based on Application Model Enrichment , 2011, Int. J. Cooperative Inf. Syst..

[9]  S. Krause,et al.  OverSim: A Flexible Overlay Network Simulation Framework , 2007, 2007 IEEE Global Internet Symposium.

[10]  Gerti Kappel,et al.  Cloud Modeling Languages by Example , 2014, 2014 IEEE 7th International Conference on Service-Oriented Computing and Applications.

[11]  Gerti Kappel,et al.  UML-based Cloud Application Modeling with Libraries, Profiles, and Templates , 2014, CloudMDE@MoDELS.

[12]  András Varga,et al.  An overview of the OMNeT++ simulation environment , 2008, SimuTools.

[13]  Rajkumar Buyya,et al.  Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities , 2009, 2009 International Conference on High Performance Computing & Simulation.

[14]  Ondrej Rysavý,et al.  Skip This Paper - RINASim: Your Recursive InterNetwork Architecture Simulator , 2015, ArXiv.

[15]  Xiangke Liao,et al.  Resource stealing: a resource multiplexing method for mix workloads in cloud system , 2015, The Journal of Supercomputing.

[16]  Douglas C. Schmidt,et al.  Guest Editor's Introduction: Model-Driven Engineering , 2006, Computer.

[17]  Ling Liu,et al.  Augmenting Amdahl's Second Law: A Theoretical Model to Build Cost-Effective Balanced HPC Infrastructure for Data-Driven Science , 2017, 2017 IEEE 10th International Conference on Cloud Computing (CLOUD).

[18]  Tom Mens,et al.  A Taxonomy of Model Transformation , 2006, GRaMoT@GPCE.

[19]  Rawya Rizk,et al.  Smart elastic scheduling algorithm for virtual machine migration in cloud computing , 2019, The Journal of Supercomputing.

[20]  Kyoungho An,et al.  Model-driven performance estimation, deployment, and resource management for cloud-hosted services , 2013, DSM '13.

[21]  Oliver Kopp,et al.  Vino4TOSCA: A Visual Notation for Application Topologies Based on TOSCA , 2012, OTM Conferences.

[22]  Henri Casanova,et al.  SimGrid: A Generic Framework for Large-Scale Distributed Experiments , 2008, Tenth International Conference on Computer Modeling and Simulation (uksim 2008).

[23]  Mercedes G. Merayo,et al.  Mutomvo: Mutation testing framework for simulated cloud and HPC environments , 2018, J. Syst. Softw..

[24]  Dimitrios Tzovaras,et al.  A review of cloud computing simulation platforms and related environments , 2017, CLOSER 2017.

[25]  Carlos Canal,et al.  A UML Profile for Modeling Multicloud Applications , 2013, ESOCC.

[26]  Tony Clark,et al.  Model-driven development - Guest editor's introduction , 2003 .

[27]  Stephen J. Mellor,et al.  Model-driven development - Guest editor's introduction , 2003 .

[28]  Eunmi Choi,et al.  Study and Comparison of Virtual Machine Scheduling Algorithms in Open Source Clouds , 2016 .

[29]  Silvana Rossetto,et al.  Modeling and automatic code generation for wireless sensor network applications using model-driven or business process approaches: A systematic mapping study , 2017, J. Syst. Softw..

[30]  Antonio Brogi,et al.  ToscaMart: A method for adapting and reusing cloud applications , 2016, J. Syst. Softw..

[31]  Robert M. Hierons,et al.  A methodology for validating cloud models using metamorphic testing , 2015, Ann. des Télécommunications.

[32]  Gianna Reggio,et al.  Unit Testing of Model to Text Transformations , 2014, AMT@MoDELS.

[33]  Dzmitry Kliazovich,et al.  GreenCloud: a packet-level simulator of energy-aware cloud computing data centers , 2010, The Journal of Supercomputing.

[34]  Alexandru Iosup,et al.  C-Meter: A Framework for Performance Analysis of Computing Clouds , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.

[35]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[36]  Anneke Kleppe,et al.  MDA explained - the Model Driven Architecture: practice and promise , 2003, Addison Wesley object technology series.

[37]  Jesús Carretero,et al.  New techniques for simulating high performance MPI applications on large storage networks , 2008, 2008 IEEE International Conference on Cluster Computing.

[38]  María Emilia Cambronero,et al.  A Framework for Modeling Cloud Infrastructures and User Interactions , 2019, IEEE Access.

[39]  Jesús Carretero,et al.  E-mc2: A formal framework for energy modelling in cloud computing , 2013, Simul. Model. Pract. Theory.

[40]  Fairouz Fakhfakh,et al.  Simulation tools for cloud computing: A survey and comparative study , 2017, 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS).

[41]  Jochen Malte Küster,et al.  Validation of model transformations: first experiences using a white box approach , 2006, MoDELS'06.