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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/18276
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dc.contributor.authorKiss, T-
dc.contributor.authorDesLauriers, J-
dc.contributor.authorGesmier, G-
dc.contributor.authorTerstyanszky, G-
dc.contributor.authorPierantoni, G-
dc.contributor.authorAbu Oun, O-
dc.contributor.authorTaylor, SJE-
dc.contributor.authorAnagnostou, A-
dc.contributor.authorKovacs, J-
dc.date.accessioned2019-05-31T10:03:38Z-
dc.date.available2019-05-31T10:03:38Z-
dc.date.issued2019-06-03-
dc.identifier.citationKiss, T., DesLauriers, J., Gesmier, G., Terstyanszky, G., Pierantoni, G., Oun, O.A., Taylor, S.J.E., Anagnostou, A. and Kovacs, J. (2019) 'A cloud-agnostic queuing system to support the implementation of deadline-based application execution policies', Future Generation Computer Systems, 101, pp. 99-111. doi: 10.1016/j.future.2019.05.062.en_US
dc.identifier.issn0167-739X-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/18276-
dc.description.sponsorshipCOLA Cloud Orchestrationen_US
dc.description.sponsorshipEuropean Commission through COLA Cloud Orchestration at the level of Applications Project No. 731574.-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsThis is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by- nc- nd/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by- nc- nd/4.0/-
dc.subjectcloud computingen_US
dc.subjectcontainer technologiesen_US
dc.subjectdeadline-based auto-scalingen_US
dc.subjectJQueueren_US
dc.subjectMiCADOen_US
dc.subjectagent-based simulationen_US
dc.titleA Cloud-agnostic Queuing System to Support the Implementation of Deadline-based Application Execution Policiesen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.future.2019.05.062-
dc.relation.isPartOfFuture Generation Computer Systems-
pubs.publication-statusPublished-
dc.identifier.eissn1872-7115-
dcterms.abstractThere are many scientific and commercial applications that require the execution of a large number of independent jobs resulting in significant overall execution time. Therefore, such applications typically require distributed computing infrastructures and science gateways to run efficiently and to be easily accessible for end-users. Optimising the execution of such applications in a cloud computing environment by keeping resource utilisation at minimum but still completing the experiment by a set deadline has paramount importance. As container-based technologies are becoming more widespread, support for job-queuing and auto-scaling in such environments is becoming important. Current container management technologies, such as Docker Swarm or Kubernetes, while provide auto-scaling based on resource consumption, do not support job queuing and deadline-based execution policies directly. This paper presents JQueuer, a cloud-agnostic queuing system that supports the scheduling of a large number of jobs in containerised cloud environments. The paper also demonstrates how JQueuer, when integrated with a cloud application-level orchestrator and auto-scaling framework, called MiCADO, can be used to implement deadline-based execution policies. This novel technical solution provides an important step towards the cost-optimisation of batch processing and job submission applications. In order to test and prove the effectiveness of the solution, the paper presents experimental results when executing an agent-based simulation application using the open source REPAST simulation framework.-
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