A Learning-Based Wireless Network Operating System with Autonomous Distributed Network Control
Abstract
A core problem in tactical wireless networks is to translate commander~s intent, often expressed in terms of tasks that require timely and guaranteed response, into a set of policies - and eventually a set of distributed control actions - that can provide high throughput and reliable information gathering and delivery, sometimes in the presence of uncertainty and adversarial actions. This is often difficult because of the distributed nature of the network control problemand of the challenging battlefield conditions. The objective of this proposal is to set the foundation to establish an applied research program to develop the core building blocks for a new autonomous network management system - rooted innonlinear optimization and learning theory - for tactical wireless networks, based on which the commander~s intent can be translated, in an automated manner, into distributed optimal network operating policies.This new framework will build (and significantly improve upon) a new principled softwaredefined networking framework, the Wireless Network Operating System (WNOS), that has been developed by the PI of this proposal in previous ONR-funded research.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 13, 2019
- Source ID
- N000141912409
Entities
People
- Tommaso Melodia
Organizations
- Northeastern University
- Office of Naval Research
- United States Navy