The ResNet project aims to enhance the integrity and resilience of communication networks within highly dynamic operational environments. To achieve this goal, we are leveraging cutting-edge network technology to facilitate anomaly detection and predictive analytics, enabling real-time optimisation in both cyber and physical systems. Our methodology is designed to tackle three key challenges:

• Network Performance Diagnostics: We are considering spatiotemporal constraints to develop innovative network modelling techniques.
• Predictive Control of Network Maintenance and Operations: We are implementing a distributed decision-making framework to improve the predictive control of network maintenance and operational processes.
• Autonomic Control System for Resilient Networks: We are developing agent-based models that autonomously handle diagnostics, prognostics, and predictive control.

Our approach involves a series of tasks aimed at defining the scope of ResNet as well as at creating mathematical models and practical tools for diagnostics and control within specific communication networks at Boeing. We will focus on prioritising critical problem areas and the development and testing of solution prototypes. 

People

Prof. Ajith Kumar Parlikad

Dr. Manuel Herrera

Dr. Aitichya Chandra

Project partner

Boeing Research & Technology