papertopic.md

ORAN-MEC Towards Point Cloud Streaming Application

Overview

This paper explores the integration of Open Radio Access Network (ORAN) and Multi-Access Edge Computing (MEC) to enable a Point Cloud Streaming (PCS) application for robotic control. The proposed architecture leverages edge computing to process point cloud data from robots, ensuring low latency and efficient real-time decision-making.

System Architecture

• Robots stream data: Robots continuously transmit point cloud data to movement controllers running as services in MEC.
• MEC-hosted movement controllers: The movement controllers, deployed as services in MEC, process the point cloud data to make movement decisions for robots.
• Data Center computing offload: The Data Center offloads computing tasks to MEC to enhance the efficiency and responsiveness of movement controllers.
• Point Cloud AF Controller (PCAF):
  • Determines which services in MEC are optimal for handling point cloud streams.
  • Influences traffic in the 5G Core to dynamically register robots with the most suitable movement controllers running in MEC.

Procedure Description

1. Data Transmission
   • Robots collect and stream point cloud data to the network.
   • Data flows through ORAN taking advantages of benefits from ORAN for low-latency streaming.
2. Traffic Influence & Service Optimization
   • The Point Cloud AF Controller (PCAF) assesses traffic conditions and determines the most suitable MEC-hosted movement controller.
   • PCAF influences the 5G Core to register robots with the optimal service in MEC in Userplane Session Establishment.
3. Edge Processing at MEC
   • Movement controllers in MEC process point cloud data in real-time.
   • MEC services optimize movement decisions and send commands back to robots.
4. Computing Offloading
   • If required, MEC offloads computation-heavy tasks to the Data Center.
   • The Data Center provides additional processing power while MEC ensures real-time responsiveness.
5. Decision Execution
   • Robots receive movement instructions based on processed point cloud data.
   • The loop continues to ensure smooth robotic operations.

Contributions

Our key contributions include:

1. Streaming Program: A dedicated streaming mechanism optimized for point cloud data transmission.
2. Point Cloud AF Controller (PCAF): A novel approach to selecting optimal MEC services and influencing 5G Core traffic.
3. MEC Implementation: Deployment of movement controllers as services within MEC to support real-time robotic movement decisions.