Title :
Job Scheduling with License Reservation: A Semantic Approach
Author :
Ejarque, Jorge ; Micsik, Andras ; Sirvent, Raül ; Pallinger, Peter ; Kovacs, Laszlo ; Badia, Rosa M.
Author_Institution :
Grid Comput. & Clusters Group, Barcelona Supercomput. Center (BSC), Barcelona, Spain
Abstract :
The license management is one of the main concerns when Independent Software Vendors (ISV) try to distribute their software in computing platforms such as Clouds. They want to be sure that customers use their software according to their license terms. The work presented in this paper tries to solve part of this problem extending a semantic resource allocation approach for supporting the scheduling of job taking into account software licenses. This approach defines the licenses as another type of computational resource which is available in the system and must be allocated to the different jobs requested by the users. License terms are modeled as resource properties, which describe the license constraints. A resource ontology has been extended in order to model the relations between customers, providers, jobs, resources and licenses in detail and make them machine processable. The license scheduling has been introduced in a semantic resource allocation process by providing a set of rules, which evaluate the semantic license terms during the job scheduling.
Keywords :
DP industry; cloud computing; law; resource allocation; scheduling; cloud computing platforms; independent software vendors; job scheduling; license management; license reservation; semantic resource allocation approach; software licenses; Law; Licenses; Ontologies; Processor scheduling; Resource management; Semantics; Software; cloud computing; distributed systems; grid computing; multi-agent; resource allocation; scheduling; semantics; software licenses;
Conference_Titel :
Parallel, Distributed and Network-Based Processing (PDP), 2011 19th Euromicro International Conference on
Conference_Location :
Ayia Napa
Print_ISBN :
978-1-4244-9682-2
DOI :
10.1109/PDP.2011.24