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Integration and Evaluation of Decentralized Fairshare Prioritization (Aequus)
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Fairshare is commonly one of the factors used by cluster resource management systems to prioritize jobs during scheduling. Despite the grid vision of a transparent and unified infrastructure, fairshare is normally calculated and enforced at the local cluster level rather than at a grid-wide scale. Aequus is a self-contained decentralized system for grid-wide fairshare job prioritization. Using Aequus, detailed global share policies can be combined with local cluster policies to offer a unified grid fairshare prioritization system where local administrations retain control over their clusters. This work shows how Aequus can be integrated with local resource management systems such as SLURM and Maui with minimal intrusion. Early results from production use are presented, and the system is further tested and evaluated for use at a nation-wide scale. Statistical models are created based on historical national grid usage data, and synthetic traces based on these models are used to create a diverse input set used to exemplify system behavior. The system is shown to behave consistently despite great variations in job arrival patterns and partial participation of some of the collaborating installations.

Keyword [en]
Grid scheduling, Fairshare scheduling, Workload modeling
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-80126OAI: oai:DiVA.org:umu-80126DiVA: diva2:646910
Conference
19th IEEE International Conference on Parallel and Distributed Systems
Funder
Swedish Research Council, C0590801eSSENCE - An eScience Collaboration
Note

Submitted 2013

Available from: 2013-09-10 Created: 2013-09-10 Last updated: 2013-09-19Bibliographically approved
In thesis
1. Enabling Technologies for Management of Distributed Computing Infrastructures
Open this publication in new window or tab >>Enabling Technologies for Management of Distributed Computing Infrastructures
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Computing infrastructures offer remote access to computing power that can be employed, e.g., to solve complex mathematical problems or to host computational services that need to be online and accessible at all times. From the perspective of the infrastructure provider, large amounts of distributed and often heterogeneous computer resources need to be united into a coherent platform that is then made accessible to and usable by potential users. Grid computing and cloud computing are two paradigms that can be used to form such unified computational infrastructures.

Resources from several independent infrastructure providers can be joined to form large-scale decentralized infrastructures. The primary advantage of doing this is that it increases the scale of the available resources, making it possible to address more complex problems or to run a greater number of services on the infrastructures. In addition, there are advantages in terms of factors such as fault-tolerance and geographical dispersion. Such multi-domain infrastructures require sophisticated management processes to mitigate the complications of executing computations and services across resources from different administrative domains.

This thesis contributes to the development of management processes for distributed infrastructures that are designed to support multi-domain environments. It describes investigations into how fundamental management processes such as scheduling and accounting are affected by the barriers imposed by multi-domain deployments, which include technical heterogeneity, decentralized and (domain-wise) self-centric decision making, and a lack of information on the state and availability of remote resources.

Four enabling technologies or approaches are explored and developed within this work: (I) The use of explicit definitions of cloud service structure as inputs for placement and management processes to ensure that the resulting placements respect the internal relationships between different service components and any relevant constraints. (II) Technology for the runtime adaptation of Virtual Machines to enable the automatic adaptation of cloud service contexts in response to changes in their environment caused by, e.g., service migration across domains. (III) Systems for managing meta-data relating to resource usage in multi-domain grid computing and cloud computing infrastructures. (IV) A global fairshare prioritization mechanism that enables computational jobs to be consistently prioritized across a federation of several decentralized grid installations.

Each of these technologies will facilitate the emergence of decentralized computational infrastructures capable of utilizing resources from diverse infrastructure providers in an automatic and seamless manner.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2013. 64 p.
Series
Report / UMINF, ISSN 0348-0542 ; 13.19
Keyword
grid computing, cloud computing, accounting, billing, contextualization, monitoring, structure, fairshare, scheduling, federated
National Category
Computer Science
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-80129 (URN)978-91-7459-704-2 (ISBN)
Public defence
2013-10-17, KBC-huset, Stora hörsalen KBC, KB3B1, Umeå Universitet, Umeå, 13:15 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, 215605EU, FP7, Seventh Framework Programme, 257115Swedish Research Council, 621-2005-3667eSSENCE - An eScience Collaboration
Note

Note that the author changed surname from Henriksson to Espling in 2011

Available from: 2013-09-23 Created: 2013-09-10 Last updated: 2013-09-19Bibliographically approved

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Espling, DanielÖstberg, Per-OlovElmroth, Erik

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