TY - JOUR
T1 - An ontology for heterogeneous resources management interoperability and HPC in the cloud
AU - Castañé, Gabriel G.
AU - Xiong, Huanhuan
AU - Dong, Dapeng
AU - Morrison, John P.
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/11
Y1 - 2018/11
N2 - The ever-increasing number of customers that have been using cloud computing environments is driving heterogeneity in the cloud infrastructures. The incorporation of heterogeneous resources to traditional homogeneous infrastructures is supported by specific resource managers cohabiting with traditional resource managers. This blend of resource managers raises interoperability issues in the Cloud management domain as customer services are exposed to disjoint mechanisms and incompatibilities between APIs and interfaces. In addition, deploying and configuring HPC workloads in such environments makes porting HPC applications, from traditional cluster environments to the Cloud, complex and ineffectual. Many efforts have been taken to create solutions and standards for ameliorating interoperability issues in inter-cloud and multi-cloud environments and parallels exist between these efforts and the current drive for the adoption of heterogeneity in the Cloud. The work described in this paper attempts to exploit these parallels; managing interoperability issues in Cloud from a unified perspective. In this paper the mOSAIC ontology, pillar of the IEEE 2302 — Standard for Intercloud Interoperability and Federation, is extended towards creating the CloudLightning Ontology (CL-Ontology), in which the incorporation of heterogeneous resources and HPC environments in the Cloud are considered. To support the CL-Ontology, a generic architecture is presented as a driver to manage heterogeneity in the Cloud and, as a use case example of the proposed architecture, the internal architecture of the CloudLightning system is redesigned and presented to show the feasibility of incorporating a semantic engine to alleviate interoperability issues to facilitate the incorporation of HPC in Cloud.
AB - The ever-increasing number of customers that have been using cloud computing environments is driving heterogeneity in the cloud infrastructures. The incorporation of heterogeneous resources to traditional homogeneous infrastructures is supported by specific resource managers cohabiting with traditional resource managers. This blend of resource managers raises interoperability issues in the Cloud management domain as customer services are exposed to disjoint mechanisms and incompatibilities between APIs and interfaces. In addition, deploying and configuring HPC workloads in such environments makes porting HPC applications, from traditional cluster environments to the Cloud, complex and ineffectual. Many efforts have been taken to create solutions and standards for ameliorating interoperability issues in inter-cloud and multi-cloud environments and parallels exist between these efforts and the current drive for the adoption of heterogeneity in the Cloud. The work described in this paper attempts to exploit these parallels; managing interoperability issues in Cloud from a unified perspective. In this paper the mOSAIC ontology, pillar of the IEEE 2302 — Standard for Intercloud Interoperability and Federation, is extended towards creating the CloudLightning Ontology (CL-Ontology), in which the incorporation of heterogeneous resources and HPC environments in the Cloud are considered. To support the CL-Ontology, a generic architecture is presented as a driver to manage heterogeneity in the Cloud and, as a use case example of the proposed architecture, the internal architecture of the CloudLightning system is redesigned and presented to show the feasibility of incorporating a semantic engine to alleviate interoperability issues to facilitate the incorporation of HPC in Cloud.
KW - Cloud interoperability
KW - HPC in cloud
KW - Ontology
KW - Resource management
KW - Self-management clouds
UR - http://www.scopus.com/inward/record.url?scp=85048744854&partnerID=8YFLogxK
U2 - 10.1016/j.future.2018.05.086
DO - 10.1016/j.future.2018.05.086
M3 - Article
AN - SCOPUS:85048744854
SN - 0167-739X
VL - 88
SP - 373
EP - 384
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -