Ordering for Hypothesis Testing and Beyond

Abstract

In this project, we have developed novel distributed processing approaches which can reduce the number of required communications in many applications. The distributed processing approaches that are popular with the research community require a very large number of communications and this has a number of disadvantages. The Army has many applications which employ wireless communications between battery powered nodes. In these applications, communications are typically one of the largest sources of energy usage. Thus, these excessive communications tend to drain the batteries and this can have serious negative impact on battlefield superiority. On the other hand, the latency for typical computing units to send data over a standard wired network connection is around 2500 times larger than that for accessing data in its own main memory. Thus reducing the number of communications can provide much faster results. This project seeks to develop methods which would allow the number of communications to be dramatically reduced with no significant loss in performance when compared to the performance of the best full-communication approaches.

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Document Details

Document Type
Technical Report
Publication Date
Nov 08, 2021
Accession Number
AD1208009

Entities

People

  • Rick Blum

Organizations

  • Lehigh University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Change Detection
  • Code Division Multiple Access
  • Detection
  • Detectors
  • Doppler Effect
  • Heterogeneous Networks
  • Information Processing
  • Information Science
  • Modulation
  • Multiple Access
  • Multiple Input Multiple Output
  • Orthogonal Frequency Division Multiplexing
  • Probability Density Functions
  • Sensor Networks
  • Signal Detection
  • Signal Processing
  • Wireless Communications
  • Wireless Sensor Networks

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Networking
  • Parallel and Distributed Computing.
  • Systems Analysis and Design