Important Dates
Paper Submission: March 30th, 2026
Notification of Acceptance: April 27th, 2026
Camera-ready Submission: May 4th, 2026
Workshop Date: Monday June 29th, 2026
Call for Papers
Aim and Scope
The 5th International Workshop on Edge Network Softwarization (ENS 2026) will be co-hosted at the 12th IEEE International Conference on Network Softwarization, which will be held from June 29th to July 3rd, 2026 in Berlin, Germany.
The workshop aims at providing an overview of the softwarization process and application of AI that has started occurring in recent years and is involving the network edge, with a focus on future-proof approaches that will be part of the advanced 5G&B and 6G network solutions.
Edge network softwarization is a fundamental topic that has to be thoroughly investigated to allow the deployment of future networks characterized by reliability and robustness.
Topics of Interest
The topics of interest for ENS 2026 include, but are not limited to:
SDN and NFV distributed solutions for the network edge in 5G&B and 6G networks;
Software-Defined Wide Area Network (SD-WAN) solutions for network edge;
Service and network orchestration at the edge;
Novel solutions for data-plane programmable (e.g. P4, eBPF, XDP) edge devices;
Artificial Intelligence and Machine Learning at the edge;
Serverless computing and Function-as-a-Service in edge and fog network architectures;
Network-aware resource provisioning in Fog Computing;
Advances to end-to-end tunneling technologies (e.g., VxLAN, IPSEC/GRE);
Edge computing energy efficiency and resource optimisation;
Support for low-latency applications at the edge (e.g., Tactile Internet);
Edge-driven use cases (e.g., Agriculture 4.0, Industry 4.0, etc.);
Privacy and security for the network edge (e.g., zero trust networks);
Multi-tenancy of edge networks;
Network edge availability and protection;
Open Hardware and Software solutions;
Converged optical and wireless architectures at the edge;
AI-powered resource allocation and energy optimization at the edge;
AI for automatic fault recovery of edge computing resources;
AI-based Digital Twin application for networked services.