Dyna-5G: A Dynamic, Flexible, and Self-Organizing 5G Network for M2M Ecosystems

TL;DR

Dyna-5G, a dynamic, self-organizing 5G New Radio (5G-NR) network designed for massive Machine-to-Machine (M2M) networks, is presented, indicating that the entire 5G network model can fully re-organize in 6 seconds at maximum, without compromising the mission.

Abstract

In this work, we present Dyna-5G, a dynamic, self-organizing 5G New Radio (5G-NR) network designed for massive Machine-to-Machine (M2M) networks. Traditional 5G NR networks, characterized by their centralized architecture, face challenges in supporting applications that require dynamic, decentralized communication, such as autonomous vehicles and drone swarms for emergency responses. These scenarios often suffer from the centralized model's single point of failure, undermining the reliability required in critical and fully autonomous applications. Dyna-5G addresses these challenges by allowing each device in the network to function as either part of the Radio Access Network (RAN) and Core Network, or as User Equipment (UE), thus maintaining network functionality even when conventional infrastructure components are compromised. Dyna-5G has built-in mechanisms carefully designed specifically for M2M networks, such as failure-recovery and ad-hoc entry and exit. We demonstrate the performance and feasibility of Dyna-5G using a custom-built testbed that simulates real-world missions, demonstrating our network's robustness, adaptability, and failure recovery capabilities. The results indicate that our entire 5G network model can fully re-organize in 6 seconds at maximum, without compromising the mission.

Figures (17)

• Figure 1: The drones execute a mission (blue shows the trajectory), when the leader fails unexpectedly. The network reorganizes with a new leader (#4) as it reaches the destination. The golden star denotes the leader (5GC & RAN), whereas silver star indicates the follower (UE).
• Figure 2: Components placed at each machine. The leader enables the 5G Core and RAN parts, while the follower the User Equipment. The Network table and Application Server are always operational for communication and (re)organization. The State Controller handles all the components and makes the proper decision.
• Figure 3: State diagram for all machines in the network. Arrows denote the Event which triggers each state change.
• Figure 4: UE-Drone establishing connection with the network. The RAN and Core are hosted by another drone, which has been selected as network leader.
• Figure 5: Operations between two machines. Both machines exchange heartbeat notifications (1), execute their performance evaluations (2a) and share the performance reports (2b), and complete the leader selection process (3).