A Research Proposal on Cognitive Opportunistic Communications and Cognitive Cross-layer Protocol Stack Design

Abstract

The specific aims of the project include: (i) to propose a Cognitive Network concept by applying the cognition loop both to the in-stack (from MAC to Transport layer) and the out-stack parameters using probabilistic graphical models and (ii) to create opportunistic solutions for cross layer cognitive networking. We propose to use a novel approach based on Bayesian Networks (BNs) that can capture the dependency between network protocol parameters across the stack exploiting the historical behavior of the observed data. We also proposed and prototyped a Cognitive Access Point (CogAP) that utilized the out- stack BN model. Furthermore, we investigated cross layer solutions for implementing a distributed control channel and a neighbor discovery mechanism that is robust against jamming attacks, studying the problem both with a theoretical and a simulative approach. We concluded our work with a practical case of study, in which we observed the challenges in gathering network traffic information from an emergency response network and we studied three physical world events where we conducted passive network traffic measurements to study the interaction between physical and cyber worlds.

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Document Details

Document Type
Technical Report
Publication Date
Jul 23, 2012
Accession Number
ADA584715

Entities

People

  • B. S. Manoj
  • Michele Zorzi
  • Ramesh Rao

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Counter WMD
  • Cyber
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Cognitive Radio
  • Communication Systems
  • Computer Networks
  • Computer Programming
  • Computers
  • Digital Information
  • First Responders
  • Information Theory
  • Network Protocols
  • Probability
  • Students
  • Transport Protocols
  • Wireless Communications
  • Wireless Computer Networks
  • Wireless Mesh Networks
  • Wireless Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • Cyber