The Workshop on Measurements for Self-Driving Networks will be held in Orlando, Florida, USA, on June 19, 2023, in conjunction with ACM Sigmetrics 2023. The Call for (Short) Papers is now active at: https://measure-selfdn23.cs.ucsb.edu/#call-for-short-papers
This workshop will provide a forum for researchers to present and share their latest research on new technologies that can help realize practical, deployable self-driving networks. This workshop seeks contributions from experts in networking, machine learning (applied and theoretical), network security, control theory, distributed systems, computer architecture, data science, etc., who share in the excitement of realizing the vision of self-driving networks. Strong preference will be given to research papers that describe original ideas related to the design of scalable and robust systems for monitoring and measuring network state and the development of production-ready ML-based tools that focus on explainability, trustworthiness, safety, etc., and enable the type of high-stakes decision making that self-driving networks demand.
Submissions related to all aspects of designing and building self-driving networks are welcome. Topics of special interest include
* Flexible collection of diverse and high-quality data from realistic network environments
* Design of in-network measurement architectures
* Design, implementation, and deployment of testbeds for self-driving networks
* Automated closed-loop traffic-engineering systems (e.g., routing, machine-learned TCP, or hypervisor rate controllers)
* Development of trustworthy ML models for inferring (and subsequently mitigating) network attacks or network performance issues
* New machine learning problems and questions that arise from network operations tasks that are related to performance or security
* Network measurement techniques that adapt collection or measurement based on changing network conditions
* New algorithms for performing approximate queries (with accuracy guarantees) and dynamic queries
* Robust architectures for fine-grained and programmable network monitoring
* Design and implementation of closed-loop feedback control for ensuring system robustness to uncertainties in the environment
* Examples of design choices informed by control-theoretic findings (e.g., hard limits, unavoidable tradeoffs)
* AI/ML-based production-ready (i.e., explainable, trustworthy, safe) solutions for different management and control tasks (e.g., congestion control, QoS/QoE optimization, network security, packet scheduling, traffic classification, device fingerprinting, etc.)
In addition to presenting 3-page short papers, the workshop will include presentations from invited speakers, a panel discussion, and technical discussions between speakers and workshop participants.
** Important Dates **
* Paper submission: April 29, 2023
* Author notification: May 13, 2023
* Final version submission: May 30, 2023
* Workshop: June 19, 2023
Please check the workshop's website for more details: measure-selfdn23.cs.ucsb.edu/.
** Note **
We will offer travel support (including the conference registration fee) for all speakers and panelists for this workshop.
Best Regards,
ACM SIGMETRICS 2023 Organizing Team
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