Smart Cloud Engine and Solution Based on Knowledge Base

Abstract Complexity of cloud infrastructures needs models and tools for process management, configuration, scaling, elastic computing and healthiness control. This paper presents a Smart Cloud solution based on a Knowledge Base, KB, with the aim of modeling cloud resources, Service Level Agreements and their evolution, and enabling the reasoning on structures by implementing strategies of efficient smart cloud management and intelligence. The solution proposed provides formal verification tools and intelligence for cloud control. It can be easily integrated with any cloud configuration manager, cloud orchestrator, and monitoring tool, since the connections with these tools are performed by using REST calls and XML files. It has been validated in the large ICARO Cloud project with a national cloud service provider.

[1]  Yueming Lu,et al.  Dynamic Task Scheduling in Cloud Computing Based on Greedy Strategy , 2012, ISCTCS.

[2]  Pierfrancesco Bellini,et al.  Linked open graph: Browsing multiple SPARQL entry points to build your own LOD views , 2014, J. Vis. Lang. Comput..

[3]  Salvatore Venticinque,et al.  An SLA-based Broker for Cloud Infrastructures , 2013, Journal of Grid Computing.

[4]  Jyh-Horng Chou,et al.  Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm , 2013, Comput. Oper. Res..

[5]  Ian Sommerville,et al.  QoSOnt: a QoS ontology for service-centric systems , 2005, 31st EUROMICRO Conference on Software Engineering and Advanced Applications.

[6]  Rocco Aversa,et al.  Proceedings of the Federated Conference on Computer Science and Information Systems pp. 973–980 ISBN 978-83-60810-22-4 An Analysis of mOSAIC ontology for Cloud Resources annotation , 2022 .

[7]  Rajkumar Buyya,et al.  Service Level Agreement (SLA) in Utility Computing Systems , 2010, ArXiv.

[8]  David Bernstein,et al.  Using Semantic Web Ontology for Intercloud Directories and Exchanges , 2010, International Conference on Internet Computing.

[9]  Paolo Nesi,et al.  Cloud Knowledge Modeling and Management , 2015 .

[10]  Heiko Ludwig,et al.  Web Service Level Agreement (WSLA) Language Specification , 2003 .

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

[12]  Amit P. Sheth,et al.  Semantic WS-agreement partner selection , 2006, WWW '06.

[13]  L. Youseff,et al.  Toward a Unified Ontology of Cloud Computing , 2008, 2008 Grid Computing Environments Workshop.

[14]  Cees T. A. M. de Laat,et al.  Towards an Infrastructure Description Language for Modeling Computing Infrastructures , 2012, 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications.

[15]  Jurica Ševa,et al.  Cloud Computing Ontologies: A Systematic Review , 2012 .

[16]  Adam Barker,et al.  Observing the clouds: a survey and taxonomy of cloud monitoring , 2014, Journal of Cloud Computing.

[17]  Armin Haller,et al.  An ontology-based system for Cloud infrastructure services' discovery , 2012, 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom).

[18]  Saswati Mukherjee,et al.  Efficient Task Scheduling Algorithms for Cloud Computing Environment , 2011, HPAGC.

[19]  Asit Dan,et al.  Web services agreement specification (ws-agreement) , 2004 .

[20]  Jorge S. Cardoso,et al.  Linked USDL: A Vocabulary for Web-Scale Service Trading , 2014, ESWC.

[21]  Jiao Tao,et al.  Towards Integrity Constraints in OWL , 2009, OWLED.

[22]  Frank Leymann,et al.  Portable Cloud Services Using TOSCA , 2012, IEEE Internet Computing.

[23]  Calton Pu,et al.  Intelligent management of virtualized resources for database systems in cloud environment , 2011, 2011 IEEE 27th International Conference on Data Engineering.