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Virtual Machine Placement in Cloud Environments
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

With the emergence of cloud computing, computing resources (i.e., networks, servers, storage, applications, and services) are provisioned as metered on-demand services over networks, and can be rapidly allocated and released with minimal management effort. In the cloud computing paradigm, the virtual machine is one of the most commonly used resource carriers in which business services are encapsulated. Virtual machine placement optimization, i.e., finding optimal placement schemes for virtual machines, and reconfigurations according to the changes of environments, become challenging issues.

The primary contribution of this licentiate thesis is the development and evaluation of our combinatorial optimization approaches to virtual machine placement in cloud environments. We present modeling for dynamic cloud scheduling via migration of virtual machines in multi-cloud environments, and virtual machine placement for predictable and time-constrained peak loads in single-cloud environments. The studied problems are encoded in a mathematical modeling language and solved using a linear programming solver. In addition to scientific publications, this work also contributes in the form of software tools (in EU-funded project OPTIMIS) that demonstrate the feasibility and characteristics of the approaches presented.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet , 2012. , 18 p.
Series
UMINF / Department of Computing Science, Umeå University, ISSN ISSN 0348-0542 ; 2012:13
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:umu:diva-83385ISBN: 978-91-7459-453-9 (print)OAI: oai:DiVA.org:umu-83385DiVA: diva2:666262
Presentation
2012-06-07, MIT-huset, MA121, Umeå universitet, Umeå, 10:05 (English)
Opponent
Supervisors
Available from: 2014-03-26 Created: 2013-11-22 Last updated: 2014-03-26Bibliographically approved
List of papers
1. Modeling for Dynamic Cloud Scheduling via Migration of Virtual Machines
Open this publication in new window or tab >>Modeling for Dynamic Cloud Scheduling via Migration of Virtual Machines
2011 (English)In: Cloud Computing Technology and Science (CloudCom), IEEE Computer Society, 2011, 163-171 p.Conference paper, Published paper (Refereed)
Abstract [en]

Cloud brokerage mechanisms are fundamental to reduce the complexity of using multiple cloud infrastructures to achieve optimal placement of virtual machines and avoid the potential vendor lock-in problems. However, current approaches are restricted to static scenarios, where changes in characteristics such as pricing schemes, virtual machine types, and service performance throughout the service life-cycle are ignored. In this paper, we investigate dynamic cloud scheduling use cases where these parameters are continuously changed, and propose a linear integer programming model for dynamic cloud scheduling. Our model can be applied in various scenarios through selections of corresponding objectives and constraints, and offers the flexibility to express different levels of migration overhead when restructuring an existing infrastructure. Finally, our approach is evaluated using commercial clouds parameters in selected simulations for the studied scenarios. Experimental results demonstrate that, with proper parametrizations, our approach is feasible.

Place, publisher, year, edition, pages
IEEE Computer Society, 2011
Keyword
cloud computing, dynamic scheduling, virtual machine placement, migration overhead, linear integer programming
National Category
Computer Science
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-50836 (URN)10.1109/CloudCom.2011.31 (DOI)978-1-4673-0090-2 (ISBN)
Conference
The 3rd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2011) November 29 - December 1, Athens, Greece
Available from: 2011-12-27 Created: 2011-12-27 Last updated: 2014-03-31Bibliographically approved
2. Virtual machine placement for predictable and time-constrained peak loads
Open this publication in new window or tab >>Virtual machine placement for predictable and time-constrained peak loads
2012 (English)In: Economics of Grids, Clouds, Systems, and Services: 8th International Workshop, GECON 2011, Paphos, Cyprus, December 5, 2011, Revised Selected Papers / [ed] Kurt Vanmechelen, Jörn Altmann, Omer F. Rana, Springer Berlin/Heidelberg, 2012, 120-134 p.Conference paper, Published paper (Refereed)
Abstract [en]

We present an approach to optimal virtual machine placement within datacenters for predicable and time-constrained load peaks. A method for optimal load balancing is developed, based on binary integer programming. For tradeoffs between quality of solution and computation time, we also introduce methods to pre-process the optimization problem before solving it. Upper bound based optimizations are used to reduce the time required to compute a final solution, enabling larger problems to be solved. For further scalability, we also present three approximation algorithms, based on heuristics and/or greedy formulations. The proposed algorithms are evaluated through simulations based on synthetic data sets. The evaluation suggests that our algorithms are feasible, and that these can be combined to achieve desired tradeoffs between quality of solution and execution time.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2012
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 7150
National Category
Computer Science
Identifiers
urn:nbn:se:umu:diva-51034 (URN)10.1007/978-3-642-28675-9_9 (DOI)3642286747 (ISBN)9783642286742 (ISBN)9783642286759 E-ISBN (ISBN)
Conference
GECON 2011 : 8th International Workshop on Economics of Grids, Clouds, Systems, and Services, December 5th, 2011 , Paphos, Cyprus
Available from: 2012-01-09 Created: 2012-01-09 Last updated: 2014-03-31Bibliographically approved
3. A General Approach to Service Deployment in Cloud Environments
Open this publication in new window or tab >>A General Approach to Service Deployment in Cloud Environments
2012 (English)In: Cloud and Green Computing (CGC 2012): 2012 Second International Conference on, IEEE Computer Society, 2012, 17-24 p.Conference paper, Published paper (Refereed)
Abstract [en]

The cloud computing landscape has recently developed into a spectrum of cloud architectures, leading to a broad range of management tools for similar operations but specialized for certain deployment scenarios. This both hinders the efficient reuse of algorithmic innovations within cloud management operations and increases the heterogeneity between different management systems. Our overarching goal is to overcome these problems by developing tools general enough to support the full range of popular architectures. In this contribution, we analyze commonalities in recently proposed cloud models (private clouds, multi-clouds, bursted clouds, federated clouds, etc.), and demonstrate how a key management functionality - service deployment - can be uniformly performed in all of these by a carefully designed system. The design of our service deployment framework is validated through a demonstration of how it can be used to deploy services, perform bursting and brokering, as well as mediate a cloud federation in the context of the OPTIMIS Toolkit.

Place, publisher, year, edition, pages
IEEE Computer Society, 2012
Keyword
Cloud Computing, Cloud Architecture, Service Deployment
National Category
Computer Science
Identifiers
urn:nbn:se:umu:diva-79784 (URN)10.1109/CGC.2012.90 (DOI)978-0-7695-4864-7 (ISBN)978-1-4673-3027-5 Print (ISBN)
Conference
the 2nd International Conference on Cloud and Green Computing, Xiangtan, 1-3 November 2012
Available from: 2013-09-02 Created: 2013-09-02 Last updated: 2014-04-14Bibliographically approved

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