Energy Efficiency in Network Slicing: Survey and Taxonomy

TL;DR

This survey provides a comprehensive review and taxonomy of strategies to enhance energy efficiency in network slicing for future mobile networks, highlighting open challenges and research directions.

Contribution

It introduces a novel taxonomy of energy-saving strategies in network slicing and identifies key open challenges for future research.

Findings

Reviewed state-of-the-art energy efficiency techniques

Developed a taxonomy organizing strategies into infrastructure, routing, and slice operation levels

Highlighted open challenges and AI-driven approaches for energy-efficient NS

Abstract

Network Slicing (NS) is a fundamental feature of 5G, 6G, and future mobile networks, enabling logically isolated virtual networks over shared infrastructure. As data demand increases and services diversify, ensuring Energy Efficiency (EE) in NS is vital (not only for operational cost savings but also to reduce the Information and Communication Technology (ICT) sector's environmental footprint). This survey addresses the need for a comprehensive and holistic perspective on energy-efficient NS by reviewing and classifying recent strategies across the NS life cycle. Our contributions are threefold: (i) a thorough review of state-of-the-art techniques aimed at reducing energy consumption in NS; (ii) a novel taxonomy that organizes strategies into infrastructure, path/route, and slice operation levels; and (iii) the identification of open challenges and research directions, with a focus on systemic, cross-layer, and AI-driven approaches. By consolidating insights from recent developments, our work bridges existing gaps in the literature, offering a structured foundation for researchers and practitioners to design, evaluate, and improve energy-efficient network slicing systems.