A tree‐based algorithm for virtual infrastructure allocation with joint virtual machine and network requirements
Summary Cloud providers have introduced the on‐demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By combining network and computing virtualization, providers allow traffic isolation between hosted VIs. Taking advantage of this oppor...
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| Published in | International journal of network management Vol. 27; no. 1; pp. np - n/a |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
01.01.2017
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1055-7148 1099-1190 |
| DOI | 10.1002/nem.1958 |
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| Abstract | Summary
Cloud providers have introduced the on‐demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By combining network and computing virtualization, providers allow traffic isolation between hosted VIs. Taking advantage of this opportunity, tenants have deployed private VIs with application‐optimized network topologies to increase quality of experience of final users. One of the main open challenges in this scenario is the allocation of physical resources to host VIs in accordance with quality of service computing (eg, virtual CPUs and memory) and network requirements (guaranteed bandwidth and specific network topology). Moreover, a VI can be allocated anywhere atop a network datacenter, and because of its NP‐hard complexity, the search for optimal solutions has a limited applicability in cloud providers as requesting users seek an immediate response. The present work proposes an algorithm to accomplish the VI allocation by applying tree‐based heuristics to reduce the search space, performing a joint allocation of computing and network resources. So as to accomplish this goal, the mechanism includes a strategy to convert physical and virtual graphs to trees, which later are pruned by a grouped accounting algorithm. These innovations reduce the number of comparisons required to allocate a VI. Experimental results indicate that the proposed algorithm finds an allocation on feasible time for different cloud scenarios and VI topologies, while maintaining a high acceptance rate and a moderate physical infrastructure fragmentation.
Aiming for virtual infrastructures allocation with joint virtual machine and network requirements atop cloud datacenters,we propose a heuristic having as premise that both graphs (virtual and physical) are represented in the form of trees (the graphs are connected and acyclic). Following this premise, strategies to reduce search space by grouping subtrees information are applied, which consequently accelerates the allocation process. Initially, the mechanism, termed VITreeM, converts both physical and virtual graphs in trees. In a second moment, the search space reduction algorithm resumes capacity information of subtrees, consequently removing the need for a deep search as a capacity summary is available at each tree element. Finally, VITreeM performs the allocation by comparing the ed representation of subtrees. |
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| AbstractList | Summary Cloud providers have introduced the on-demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By combining network and computing virtualization, providers allow traffic isolation between hosted VIs. Taking advantage of this opportunity, tenants have deployed private VIs with application-optimized network topologies to increase quality of experience of final users. One of the main open challenges in this scenario is the allocation of physical resources to host VIs in accordance with quality of service computing (eg, virtual CPUs and memory) and network requirements (guaranteed bandwidth and specific network topology). Moreover, a VI can be allocated anywhere atop a network datacenter, and because of its NP-hard complexity, the search for optimal solutions has a limited applicability in cloud providers as requesting users seek an immediate response. The present work proposes an algorithm to accomplish the VI allocation by applying tree-based heuristics to reduce the search space, performing a joint allocation of computing and network resources. So as to accomplish this goal, the mechanism includes a strategy to convert physical and virtual graphs to trees, which later are pruned by a grouped accounting algorithm. These innovations reduce the number of comparisons required to allocate a VI. Experimental results indicate that the proposed algorithm finds an allocation on feasible time for different cloud scenarios and VI topologies, while maintaining a high acceptance rate and a moderate physical infrastructure fragmentation. Summary Cloud providers have introduced the on‐demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By combining network and computing virtualization, providers allow traffic isolation between hosted VIs. Taking advantage of this opportunity, tenants have deployed private VIs with application‐optimized network topologies to increase quality of experience of final users. One of the main open challenges in this scenario is the allocation of physical resources to host VIs in accordance with quality of service computing (eg, virtual CPUs and memory) and network requirements (guaranteed bandwidth and specific network topology). Moreover, a VI can be allocated anywhere atop a network datacenter, and because of its NP‐hard complexity, the search for optimal solutions has a limited applicability in cloud providers as requesting users seek an immediate response. The present work proposes an algorithm to accomplish the VI allocation by applying tree‐based heuristics to reduce the search space, performing a joint allocation of computing and network resources. So as to accomplish this goal, the mechanism includes a strategy to convert physical and virtual graphs to trees, which later are pruned by a grouped accounting algorithm. These innovations reduce the number of comparisons required to allocate a VI. Experimental results indicate that the proposed algorithm finds an allocation on feasible time for different cloud scenarios and VI topologies, while maintaining a high acceptance rate and a moderate physical infrastructure fragmentation. Aiming for virtual infrastructures allocation with joint virtual machine and network requirements atop cloud datacenters,we propose a heuristic having as premise that both graphs (virtual and physical) are represented in the form of trees (the graphs are connected and acyclic). Following this premise, strategies to reduce search space by grouping subtrees information are applied, which consequently accelerates the allocation process. Initially, the mechanism, termed VITreeM, converts both physical and virtual graphs in trees. In a second moment, the search space reduction algorithm resumes capacity information of subtrees, consequently removing the need for a deep search as a capacity summary is available at each tree element. Finally, VITreeM performs the allocation by comparing the ed representation of subtrees. Cloud providers have introduced the on-demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By combining network and computing virtualization, providers allow traffic isolation between hosted VIs. Taking advantage of this opportunity, tenants have deployed private VIs with application-optimized network topologies to increase quality of experience of final users. One of the main open challenges in this scenario is the allocation of physical resources to host VIs in accordance with quality of service computing (eg, virtual CPUs and memory) and network requirements (guaranteed bandwidth and specific network topology). Moreover, a VI can be allocated anywhere atop a network datacenter, and because of its NP-hard complexity, the search for optimal solutions has a limited applicability in cloud providers as requesting users seek an immediate response. The present work proposes an algorithm to accomplish the VI allocation by applying tree-based heuristics to reduce the search space, performing a joint allocation of computing and network resources. So as to accomplish this goal, the mechanism includes a strategy to convert physical and virtual graphs to trees, which later are pruned by a grouped accounting algorithm. These innovations reduce the number of comparisons required to allocate a VI. Experimental results indicate that the proposed algorithm finds an allocation on feasible time for different cloud scenarios and VI topologies, while maintaining a high acceptance rate and a moderate physical infrastructure fragmentation. Aiming for virtual infrastructures allocation with joint virtual machine and network requirements atop cloud datacenters,we propose a heuristic having as premise that both graphs (virtual and physical) are represented in the form of trees (the graphs are connected and acyclic). Following this premise, strategies to reduce search space by grouping subtrees information are applied, which consequently accelerates the allocation process. Initially, the mechanism, termed VITreeM, converts both physical and virtual graphs in trees. In a second moment, the search space reduction algorithm resumes capacity information of subtrees, consequently removing the need for a deep search as a capacity summary is available at each tree element. Finally, VITreeM performs the allocation by comparing the abstracted representation of subtrees. |
| Author | Oliveira, Ramon Koslovski, Guilherme Piegas |
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Cloud providers have introduced the on‐demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a... Summary Cloud providers have introduced the on-demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a... Cloud providers have introduced the on-demand provisioning of virtual infrastructures (VIs) to deliver virtual networks of computing resources as a service. By... |
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| SubjectTerms | Algorithms allocation Allocations cloud computing cloud networking Graphs IaaS Infrastructure NaaS Network topologies Networks Searching Trees virtual infrastructures Virtual networks |
| Title | A tree‐based algorithm for virtual infrastructure allocation with joint virtual machine and network requirements |
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