Abstract
This study explores the integration of sustainable practices in the advancing domain of sixth-generation and beyond (6G+) network technologies, with a particular focus on enhancing the efficiency of search and rescue operations. It presents a comprehensive strategy for network slicing designed to bolster seamless communication and operational efficacy of emergency response teams in varied and ever-changing conditions. It presents an innovative approach to managing workload fluctuations in network slicing. Also, it introduces a new slice configuration mechanism to prioritize signals for devices within the complex, compelling, hierarchical network systems. Incorporating a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm is central to the approach, tackling the complexity of implementing effective communication strategies across multiple network layers. Our findings demonstrate a highly adaptable and real-time slice configuration technique within System of Systems (SoS) environments, offering significant enhancements in systems engineering and emergency communication management. This approach contributes to the robustness and reliability of emergency response communications and underscores the importance of integrating environmental sustainability in developing next-generation network technologies.
| Original language | English |
|---|---|
| Pages (from-to) | 1 |
| Number of pages | 1 |
| Journal | IEEE Transactions on Green Communications and Networking |
| DOIs | |
| Publication status | Accepted/In press - 2024 |
Keywords
- 6G mobile communication
- Complexity theory
- Multi-Agent Deep Deterministic Policy Gradient
- Multi-Agent Deep Reinforcement Learning
- network slice
- Network slicing
- Quality of service
- Radio access networks
- Resource management
- System of Systems
- Technological innovation
- Virtual Network Functions
