Next Generation Machine-learned Multi-modal Sensor Development

Abstract

This project focuses on utilizing Programmable Data-Plane Network (PDPN) to achieve flexible control over packet and flow levels, thus addressing current challenges within the multi-layered structure of the internet which often complicate data transfer management and degrade communication quality. By mediating between the high-level application demands for Quality of Service (QoS) and the resource management requirements at the lower layers, PDPN has a potential to significantly enhance network functionality and user experience. A critical element of this project is the establishment of a trans-Pacific PDPN testbed, which connects the Kyushu Institute of Technology (Kyutech) with the City College of New York (CCNY). This environment will enable the practical evaluation of PDPN s potential under conditions that assume real-world internet traffic scenarios, such as high bandwidth and latency environments. Using P4 programming, the project will explore innovative ways to manage network traffic more efficiently than traditional hardware-based packet processing methods.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 05, 2025
Source ID
FA23862414089

Entities

People

  • Seung Hwan Ko

Organizations

  • Air Force Office of Scientific Research
  • Seoul National University
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Cybersecurity.
  • Integrated Circuit Design and Technology.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks