MINTED: M ulticast VI rtual N e T work E mbedding in Cloud Data Centers With D elay Constraints

Network virtualization is regarded as the pillar of cloud computing, enabling the multi-tenancy concept where multiple Virtual Networks (VNs) can cohabit the same substrate network. With network virtualization, the problem of allocating resources to the various tenants, commonly known as the Virtual...

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Veröffentlicht in:IEEE transactions on communications 2015-04, Vol.63 (4), p.1291
Hauptverfasser: Ayoubi, Sara, Assi, Chadi, Shaban, Khaled, Narayanan, Lata
Format: Artikel
Sprache:eng
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Zusammenfassung:Network virtualization is regarded as the pillar of cloud computing, enabling the multi-tenancy concept where multiple Virtual Networks (VNs) can cohabit the same substrate network. With network virtualization, the problem of allocating resources to the various tenants, commonly known as the Virtual Network Embedding problem, emerges as a challenge. Its NP-Hard nature has drawn a lot of attention from the research community, many of which however overlooked the type of communication that a given VN may exhibit, assuming that they all exhibit a one-to-one (unicast) communication only. In this paper, we motivate the importance of characterizing the mode of communication in VN requests, and we focus our attention on the problem of embedding VNs with a one-to-many (multicast) communication mode. Throughout this paper, we highlight the unique properties of multicast VNs and its distinct Quality of Service (QoS) requirements, most notably the end-delay and delay-variation constraints for delay-sensitive multicast services. Further, we showcase the limitations of handling a multicast VN as unicast. To this extent, we formally define the VNE problem for Multicast VNs (MVNs) and prove its NP-Hard nature. We propose two novel approach to solve the Multicast VNE (MVNE) problem with end-delay and delay variation constraints: A 3-Step MVNE technique, and a Tabu-Search algorithm. We motivate the intuition behind our proposed embedding techniques, and provide a competitive analysis of our suggested approaches over multiple metrics and against other embedding heuristics.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2015.2404440