An Architecture-Based Autonomous Engine for Services Configuration and Deployment in Hybrid Clouds

As cloud computing offers scalability, extensibility, elasticity, flexibility and cost savings to the customers of cloud service providers, there is a growing trend towards migrating services to the cloud. Hybrid clouds, which comprise nodes both in the private cloud and in the public cloud, have emerged as a new model for service providers to deploy their services. However, to deploy services in hybrid clouds is a complex task as services are in essence distributed applications. What is more, there is heterogeneity among hybrid clouds. This article proposes an autonomous engine for services configuration and deployment in hybrid clouds. The automation is enabled by the definition of generic information model, which describes all the information relevant to the deployment and configuration of services with the same abstractions, including the required resources, service dependencies and business objectives. In addition, to shield the heterogeneity of hybrid clouds, we define mapping rules for model transformation. We also deploy a three-layer architecture application on Openstack and CloudStack to validate the correctness of our approach.

[1]  Gordon S. Blair,et al.  Summary of the workshop models@run.time at MoDELS 2006 , 2006, MoDELS'06.

[2]  Gang Huang,et al.  Runtime recovery and manipulation of software architecture of component-based systems , 2006, Automated Software Engineering.

[3]  Hui Song,et al.  SM@RT: Applying Architecture-Based Runtime Management into Internetware Systems , 2009, Int. J. Softw. Informatics.

[4]  Xing Chen,et al.  A Model-Based Autonomous Engine for Application Runtime Environment Configuration and Deployment in PaaS Cloud , 2014, 2014 IEEE 6th International Conference on Cloud Computing Technology and Science.

[5]  Hui Song,et al.  Supporting runtime software architecture: A bidirectional-transformation-based approach , 2011, J. Syst. Softw..

[6]  Félix Cuadrado,et al.  Model-based context-aware deployment of distributed systems , 2009, IEEE Communications Magazine.

[7]  Alberto Rodrigues da Silva,et al.  CMS-Based Web-Application Development Using Model-Driven Languages , 2009, 2009 Fourth International Conference on Software Engineering Advances.

[8]  Ewa Deelman,et al.  Automating Application Deployment in Infrastructure Clouds , 2011, 2011 IEEE Third International Conference on Cloud Computing Technology and Science.

[9]  Marin Litoiu,et al.  Introducing STRATOS: A Cloud Broker Service , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[10]  Daniel Grosu,et al.  An Online Mechanism for Dynamic VM Provisioning and Allocation in Clouds , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[11]  Xing Chen,et al.  Towards architecture-based management of platforms in the cloud , 2012, Frontiers of Computer Science.

[12]  Stefano Ceri,et al.  Web Modeling Language (WebML): a modeling language for designing Web sites , 2000, Comput. Networks.

[13]  Gordon S. Blair,et al.  Models@ run.time , 2009, Computer.

[14]  Ying Zhang,et al.  Model driven configuration of fault tolerance solutions for component-based software system , 2012, MODELS'12.

[15]  Xing Chen,et al.  Architecture-based integrated management of diverse cloud resources , 2014, Journal of Cloud Computing.