Algorithms for Assigning Substrate Network Resources to Virtual Network Components

By Yong Zhu, Mostafa H. Ammar. Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications, 2006

821 citations recorded by the source corpus.

Recent proposals for network virtualization provide a promising way to overcome the Internet ossification. The key idea of network virtualization is to build a diversified Internet to support a variety of network services and architectures through a shared substrate. A major challenge in network virtualization is the assigning of substrate resources to virtual networks (VN) efficiently and on-demand. This paper focuses on two versions of the VN assignment problem: VN assignment without reconfiguration (VNA-I) and VN assignment with reconfiguration (VNAII). For the VNA-I problem, we develop a basic scheme as a building block for all other advanced algorithms. Subdividing heuristics and adaptive optimization strategies are then presented to further improve the performance. For the VNA-II problem, we develop a selective VN reconfiguration scheme that prioritizes the reconfiguration of the most critical VNs. Extensive simulation experiments demonstrate that the proposed algorithms can achieve good performance under a wide range of network conditions.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/84bc0f4f8f9a43324140260170a4ffe3c69246d0

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Citations in the corpus

Efficient Mapping of Virtual Networks onto a Shared Substrate (2006, background): “proposed a set of heuristic algorithms for assigning substrate network resources to virtual networks [6].”
Virtual Network Embedding with Coordinated Node and Link Mapping (2009, methodology): “6 depict that the proposed algorithms, D-ViNE and R-ViNE, lead to better acceptance ratio as well as higher revenue than the existing algorithms (G-SP and G-MCF) through coordinated node and link mapping.”
A virtual network mapping algorithm based on subgraph isomorphism detection (2009, background): “…[10, 1, 8] or to Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.”
Virtual Network Embedding: A Survey (2013, background): “[74] Zhu and Ammar* (2006) Heuristic Uncoordinated Reduce the cost of periodic reconfigurations”
Rethinking virtual network embedding: substrate support for path splitting and migration (2008, background): “Previous research has addressed these computational challenges by restricting the problem space in one or more dimensions to enable eﬃcient heuristics [31, 13, 23, 26], at the expense of limiting the practical applicability of the solutions.”
QoS-Aware Deployment of IoT Applications Through the Fog (2017, methodology): “Solutions to Subgraph Isomorphism have been proposed in the context of Virtual Network embedding [13], [24], [25] and deployment over WAN [26], by performing node and link mapping in a single phase, as we do.”
A Distributed Virtual Network Mapping Algorithm (2008, methodology): “The selection and mapping of these clusters are in general performed by using centralized heuristic algorithms [6], [9].”
A survey of network virtualization (2010, background): “Zhu and Ammar [44] aim at achieving load balancing in the underlying physical infrastructure assuming unlimited resources.”
An Approach for Service Function Chain Routing and Virtual Function Network Instance Migration in Network Function Virtualization Architectures (2017, methodology): “F ] in the server w ∈ V PNS ; • S N ( w ) , deﬁned as the stress of the node w ∈ V PNS [30] and characterizing the server load; its value is tied to the variables A k ( w ) according to the following expression: • S L ( e ) , deﬁned as the stress of the physical network link e ∈ E PN [30] and…”
How to lease the internet in your spare time (2007, positive): “Fortunately, testbed designers and researchers have devised way s to compute efficient network embeddings, and we believe that Cabo can leverage these techniques [19, 30].”