NICOP - Massive network analytics

Abstract

Massive network analytics:Recent advances in information and communication technologies have shown dramatic improvement and unparalleled development of our networked world. Almost all humans are interconnected and beyond that, all objects of our environment are becoming networked, forming huge global systems. The objectives of this proposal are to provide scientific foundation for developing algorithms that will allow massive graphs problems to be tackled not only on expensive supercomputing infrastructure, but also on more available, off-the shelf equipment. This will be achieved by addressing four aspects: (1) Sub-linear graph algorithms, (2) Scalable graph algorithms, (3) Analytics for processes on massive networks, and (4) Local versus global metrics for massive graphs. The targeted research goals of the project are to provide scientific foundation for developing algorithms that will allow massive graphs problems to be tackled not only on expensive supercomputing infrastructure, but also on more available, off-the shelf equipment. This can be achieved by considering algorithms that are randomized and return an approximate solution rather than the exact one. The project long term vision is to develop a scientific foundation of data science for massive networks, which in turn will generate a technological leap from 1010 to 1018 in graphs size for networks analysis.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 23, 2016
Source ID
N629091612222

Entities

People

  • Ljupco Kocarev

Organizations

  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms