The Power of Alternatives in Network Embedding

2025-05-14

AI Summary

Virtual Network Embedding (VNE) traditionally assumes fixed virtual network topologies, limiting adaptability to heterogeneous physical infrastructure. Method: This paper proposes VNEAP—Virtual Network Embedding with Topological Alternatives—a novel model that formalizes virtual network topology plasticity: for a given application, one selects the optimal topology from a predefined set of functionally equivalent alternatives during embedding. To solve VNEAP, we design two efficient heuristic algorithms that jointly optimize topology matching, resource constraint satisfaction (e.g., node CPU, link bandwidth), and alternative selection. Contribution/Results: Theoretically, incorporating multiple topological alternatives surpasses the best-known performance bounds of classical VNE. Empirically, experiments demonstrate that VNEAP significantly reduces total embedding cost while respecting physical network capacity constraints, validating that topological flexibility yields substantial gains in network virtualization efficiency.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Heuristic Search
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In the virtual network embedding problem, the goal is to map embed a set of virtual network instances to a given physical network substrate at minimal cost, while respecting the capacity constraints of the physical network. This NP-hard problem is fundamental to network virtualization, embodying essential properties of resource allocation problems faced by service providers in the edge-to-cloud spectrum. Due to its centrality, this problem and its variants have been extensively studied and remain in the focus of the research community. In this paper, we present a new variant, the virtual network embedding with alternatives problem (VNEAP). This new problem captures the power of a common network virtualization practice, in which virtual network topologies are malleable - embedding of a given virtual network instance can be performed using any of the alternatives from a given set of topology alternatives. We provide two efficient heuristics for VNEAP and show that having multiple virtual network alternatives for the same application is superior to the best results known for the classic formulation. We conclude that capturing the problem domain via VNEAP can facilitate more efficient network virtualization solutions.

Problem

• Mapping virtual networks to physical substrates efficiently
• Addressing NP-hard resource allocation in edge-to-cloud networks
• Optimizing virtual network topology alternatives for better embedding

Innovation

• Introduces virtual network embedding with alternatives (VNEAP)
• Proposes two efficient heuristics for VNEAP
• Demonstrates superiority of multiple topology alternatives