A survey and taxonomy on virtual data center embedding

Hbaieb, Ameni; Khemakhem, Mahdi; Jemaa, Maher Ben

doi:10.1007/s11227-019-02854-1

Cited by 7 publications

(6 citation statements)

References 60 publications

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“…Constraints (13) ensure that the sum of the CPU requirements of each assigned VM does not exceed the capacity of corresponding PM i M P . Constraints ( 14) ensure that for each PS i S P , the sum of the memory requirements of each of the corresponding VSs and the memory requirements to act as an intermediary node in a physical path, representing the VL ðk,pÞ L v , does not exceed the PS capacity.…”

Section: Capacity Conservation Constraintsmentioning

confidence: 99%

“…• Physical data center topology: We consider the three-level VL2 tree as physical topology. 13,28 It contains a set of PMs distributed in racks connected by PSs. Each PM is configured to have 64 cores and each PS has 64GB of memory.…”

Section: Experimental Frameworkmentioning

confidence: 99%

“…• Virtual network topology: We consider two types of VDC topologies such as star and VL2 topologies. 13,28 The star topology is suitable for hosting several types of applications like web applications and MapReduce. 30 In each topology, the number of VMs in VDC requests is evenly distributed from 2 to 10.…”

Section: Experimental Frameworkmentioning

confidence: 99%

“…Currently, a large number of proposals have been put forth to address this challenge. In the survey of Hbaieb et al, 13 the VDCE problem in all its variants is discussed, taxonomic classification is suggested and current approaches proposed by scientific community are classified. However, all prior approaches have important limitations relative to the contributions of this paper.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To assess the effectiveness of the BLP‐VDCE model, we consider a set of new instances of the network‐aware VDCE problem with different sizes and types of VDC requests. In our experiments, we used the following DC network topologies: Physical data center topology: We consider the three‐level VL2 tree as physical topology 13,28 . It contains a set of PMs distributed in racks connected by PSs.…”

Section: Performance Evaluationmentioning

confidence: 99%

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Optimal network‐aware virtual data center embedding

Hbaieb

Khemakhem

2023

Int J Network Mgmt

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Summary Recently, the virtual data center embedding (VDCE) problem has drawn significant attention because of a growing need for efficient means of data center resource allocation. By ensuring a set of virtual data center (VDC) integration requests coming from his customers, among the main concern of an infrastructure provider is the maximization of the utilization rate of data center resources and benefits. However, existing VDCE solutions mostly focus on consolidating virtual machines in a single physical data center. Therefore, in this work, we improve the consolidated targets techniques, that consider only the virtual machines integration, by the consideration of network devices and fabrics (e.g., switches and paths/links). We consider new unreleased constraints such as multiple virtual nodes of the same request co‐location, and intermediate node requirements when a virtual link is mapped. To address the above problem, in this paper, we propose a binary linear programming‐based model, called BLP‐VDCE, to solve the VDCE problem with network‐aware consideration. This model ensures a simultaneous consolidated embedding of virtual nodes and virtual links. Extensive simulations show that solving the proposed BLP‐VDCE model can efficiently embed VDC requests with a high physical resource utilization rate.

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Section: Capacity Conservation Constraintsmentioning

confidence: 99%

Section: Experimental Frameworkmentioning

confidence: 99%