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Scheduling and Monitoring of Internally Structured Services in Cloud Federations
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N).
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N).
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N). (UMIT)
2011 (English)In: 2011 IEEE Symposium on Computers and Communications (ISCC), IEEE, 2011, 173-178 p.Conference paper, Published paper (Refereed)
Abstract [en]

Cloud infrastructure providers may form Cloud federations to cope with peaks in resource demand and to make large-scale service management simpler for service providers. To realize Cloud federations, a number of technical and managerial difficulties need to be solved. We present ongoing work addressing three related key management topics, namely, specification, scheduling, and monitoring of services. Service providers need to be able to influence how their resources are placed in Cloud federations, as federations may cross national borders or include companies in direct competition with the service provider. Based on related work in the RESERVOIR project, we propose a way to define service structure and placement restrictions using hierarchical directed acyclic graphs. We define a model for scheduling in Cloud federations that abides by the specified placement constraints and minimizes the risk of violating Service-Level Agreements. We present a heuristic that helps the model determine which virtual machines (VMs) are suitable candidates for migration. To aid the scheduler, and to provide unified data to service providers, we also propose a monitoring data distribution architecture that introduces cross-site compatibility by means of semantic metadata annotations.

Place, publisher, year, edition, pages
IEEE, 2011. 173-178 p.
Series
IEEE Symposium on Computers & Communications (ISCC), ISSN 1530-1346
Keyword [en]
cloud computing, scheduling, monitoring, service structure
National Category
Computer Science
Research subject
Computing Science
Identifiers
URN: urn:nbn:se:umu:diva-40268DOI: 10.1109/ISCC.2011.5984012ISI: 000298614900034ISBN: 978-1-4577-0678-3 (print)ISBN: 978-1-4577-0680-6 (print)OAI: oai:DiVA.org:umu-40268DiVA: diva2:399040
Conference
16th IEEE Symposium on Computers and Communications (lSCC)and First International Workshop on Management of Cloud Systems (MoCS 2011), Corfu, Greece, June 28-July 1, 2011
Available from: 2011-02-21 Created: 2011-02-21 Last updated: 2017-01-16Bibliographically approved
In thesis
1. Metadata Management in Multi-Grids and Multi-Clouds
Open this publication in new window or tab >>Metadata Management in Multi-Grids and Multi-Clouds
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Grid computing and cloud computing are two related paradigms used to access and use vast amounts of computational resources. The resources are often owned and managed by a third party, relieving the users from the costs and burdens of acquiring and managing a considerably large infrastructure themselves. Commonly, the resources are either contributed by different stakeholders participating in shared projects (grids), or owned and managed by a single entity and made available to its users with charging based on actual resource consumption (clouds). Individual grid or cloud sites can form collaborations with other sites, giving each site access to more resources that can be used to execute tasks submitted by users. There are several different models of collaborations between sites, each suitable for different scenarios and each posing additional requirements on the underlying technologies.

Metadata concerning the status and resource consumption of tasks are created during the execution of the task on the infrastructure. This metadata is used as the primary input in many core management processes, e.g., as a base for accounting and billing, as input when prioritizing and placing incoming task, and as a base for managing the amount of resources allocated to different tasks.

Focusing on management and utilization of metadata, this thesis contributes to a better understanding of the requirements and challenges imposed by different collaboration models in both grids and clouds. The underlying design criteria and resulting architectures of several software systems are presented in detail. Each system addresses different challenges imposed by cross-site grid and cloud architectures:

  • The LUTSfed approach provides a lean and optional mechanism for filtering and management of usage data between grid or cloud sites.

  • An accounting and billing system natively designed to support cross-site clouds demonstrates usage data management despite unknown placement and dynamic task resource allocation.

  • The FSGrid system enables fairshare job prioritization across different grid sites, mitigating the problems of heterogeneous scheduling software and local management policies.

The results and experiences from these systems are both theoretical and practical, as full scale implementations of each system has been developed and analyzed as a part of this work. Early theoretical work on structure-based service management forms a foundation for future work on structured-aware service placement in cross- site clouds. 

Place, publisher, year, edition, pages
Umeå: Umeå University, Department of Computing Science, 2011. 120 p.
Series
Report / UMINF, ISSN 0348-0542 ; 11.08
Keyword
grid computing, cloud computing, accounting, billing, metadata, monitoring, structure, fairshare, scheduling, federated
National Category
Computer Science
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-51159 (URN)978-91-7459-281-8 (ISBN)
Presentation
2011-10-06, Naturvetarhuset, N320, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2012-01-25 Created: 2012-01-11 Last updated: 2013-09-12Bibliographically approved
2. 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
3. Placement and Monitoring of Orchestrated Cloud Services
Open this publication in new window or tab >>Placement and Monitoring of Orchestrated Cloud Services
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Cloud computing offers pay-per-use on-demand access to computer resources for hosting program execution environments for software service deployment. Management of cloud resources includes determining, based on current monitored resource availability, which part(s) of a computational infrastructure should host such program execution environments in a process called placement. Our work defines directives that lets consumers of cloud resources influence placement to express relationships between cloud services (orchestration) and deployment constraints to uphold for related service components, without surrendering the ultimate control over placement from the infrastructure owner. The infrastructure owner remains free to define their policies and placement optimization criteria, e.g., to consolidate work that needs to be done to as few physical host machines as possible for power savings reasons. We show how the placement process can be adjusted to take such influence into account and validate through simulations that the adjustments produce the correct result without too large computational impact on the placement process itself. Further, we present a technique for transferring large data files between cloud data centers that operate in (separate) cloud federations that avoids repeated transfers in a delegation chain between members of (different) cloud federations. Finally, we present a non-invasive method of extracting monitoring data from a service deployed in a cloud federation, and a framework for making monitoring information available and understandable in spite of technical differences between monitoring systems used in cloud federations.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2015. 36 p.
Series
Report / UMINF, ISSN 0348-0542 ; 15.02
National Category
Computer Science
Identifiers
urn:nbn:se:umu:diva-98030 (URN)978-91-7601-205-5 (ISBN)
Presentation
2015-01-20, N230, Naturvetarhuset, Umeå universitet, Umeå, 10:15 (English)
Opponent
Supervisors
Available from: 2015-01-15 Created: 2015-01-14 Last updated: 2015-01-15Bibliographically approved

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