Workshop on Future Networks Autonomy Interoperability APIs and SLAs

Submit a paper – deadline 15 September

Due to the increased complexity and capacity of Future Networks, autonomous networking will be a key component of network operations. The complex nature of the network will allow scalable autonomous operations while maintaining the performance, security and privacy of the network. Systems-of-systems architectures will become more relevant as multiple autonomous/semi-autonomous systems adaptively seek to operate and interact with other systems. Frameworks enabling such interoperability will address the critical issues of resilience, security and reliability, and will employ operational interfaces and metrics (APIs, SLAs) to support those objectives. Artificial Intelligence and Machine Learning (AI/ML) will need to be integrated in the network flow in order to meet these objectives. From a physical layer perspective, AI/ML-based channel allocation will minimize congestion and increase throughput. With regard to networking, software-defined networking (SDN) and virtualization must automatically configure network paths and allocate resources in order to optimize traffic flow and patterns. Dynamic security is also required in order to keep the network safe. With newer market verticals such as Multi-Access Edge Computing (MEC) and massive Machine-Type Communications (mMTC), along with those in future networks, the attack surface of Future Networks will increase even further. Thus, autonomous security techniques are needed to address previous, current and future threats, while also dynamically configuring the security parameters of the network. To that end this workshop aims to invite contributions that explore how to enable effective, reliable and scalable autonomy, adaptive interoperability and APIs.

 

Workshop Chairs:
Eman Hammad  (University of Toronto, Canada); 
Mohammad N Patwary (Birmingham City University, Birmingham, United Kingdom (Great Britain)); 
Michael A. Enright (Quantum Dimension, Inc., USA); 
Ashutosh Dutta (Johns Hopkins University Applied Physics Labs (JHU/APL), USA)

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