Plan-Based Scalable Online Virtual Network Embedding
Oleg Kolosov, David Breitgand, Dean H. Lorenz, Gala Yadgar

TL;DR
This paper introduces OLIVE, a scalable online algorithm for virtual network embedding in edge computing, which uses offline aggregated demand planning to efficiently handle highly dynamic and large-scale request loads.
Contribution
The paper presents OLIVE, a novel online VNE algorithm that leverages offline aggregated demand planning to significantly improve scalability and request handling capacity.
Findings
Handles two orders of magnitude more requests per second than previous methods.
Uses offline aggregated demand to guide online embedding decisions.
Suitable for large-scale, real-time edge network environments.
Abstract
Network virtualization allows hosting applications with diverse computation and communication requirements on shared edge infrastructure. Given a set of requests for deploying virtualized applications, the edge provider has to deploy a maximum number of them to the underlying physical network, subject to capacity constraints. This challenge is known as the virtual network embedding (VNE) problem: it models applications as virtual networks, where virtual nodes represent functions and virtual links represent communication between the virtual nodes. All variants of VNE are known to be strongly NP-hard. Because of its centrality to network virtualization, VNE has been extensively studied. We focus on the online variant of VNE, in which deployment requests are not known in advance. This reflects the highly skewed and unpredictable demand intrinsic to the edge. Unfortunately, existing…
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Taxonomy
TopicsSoftware-Defined Networks and 5G · Cloud Computing and Resource Management · Caching and Content Delivery
