Network-aware virtual machine placement in cloud data centers with multiple traffic-intensive components

Following a shift from computing as a purchasable product to computing as a deliverable service to consumers over the Internet, cloud computing has emerged as a novel paradigm with an unprecedented success in turning utility computing into a reality. Like any emerging technology, with its advent, it...

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Veröffentlicht in:Computer networks (Amsterdam, Netherlands : 1999) Jg. 91; S. 508 - 527
Hauptverfasser: Ilkhechi, Amir Rahimzadeh, Korpeoglu, Ibrahim, Ulusoy, Özgür
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 14.11.2015
Elsevier Sequoia S.A
Schlagworte:
Algorithms
Cloud computing
Computation
Computer simulation
Consumers
Data centers
Demand
Experiments
Heuristic
Heuristic methods
Infrastructure
Internet
Interpersonal communication
Machinery
Mathematical models
Network congestion
Performance evaluation
Placement
Predictable flow
Satisfaction
Simulation
Sink node
Studies
Traffic engineering
Traffic flow
Utility computing
Virtual environments
Virtual machine placement
Cloud computing
Sink node
Network congestion
Virtual machine placement
Predictable flow
ISSN:1389-1286, 1872-7069
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Following a shift from computing as a purchasable product to computing as a deliverable service to consumers over the Internet, cloud computing has emerged as a novel paradigm with an unprecedented success in turning utility computing into a reality. Like any emerging technology, with its advent, it also brought new challenges to be addressed. This work studies network and traffic aware virtual machine (VM) placement in a special cloud computing scenario from a provider’s perspective, where certain infrastructure components have a predisposition to be the endpoints of a large number of intensive flows whose other endpoints are VMs located in physical machines (PMs). In the scenarios of interest, the performance of any VM is strictly dependent on the infrastructure’s ability to meet their intensive traffic demands. We first introduce and attempt to maximize the total value of a metric named “satisfaction” that reflects the performance of a VM when placed on a particular PM. The problem of finding a perfect assignment for a set of given VMs is NP-hard and there is no polynomial time algorithm that can yield optimal solutions for large problems. Therefore, we introduce several off-line heuristic-based algorithms that yield nearly optimal solutions given the communication pattern and flow demand profiles of subject VMs. With extensive simulation experiments we evaluate and compare the effectiveness of our proposed algorithms against each other and also against naïve approaches.
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ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2015.08.042