frontmatter 
title: "Network Synthesis for Tactical Environments: Scenario, Challenges, and Opportunities"
venue: SPIE Defense + Commercial Sensing
doi: 10.1117/12.2619048
date: 2022-06-06
authors:
  - Tzanis Anevlavis
  - Jonathan Bunton
  - "[[Jared Coleman]]"
  - Mine Dogan
  - Eugenio Grippo
  - Abel Souza
  - Christina Fragouli
  - Bhaskar Krishnamachari
  - Matthew Maness
  - Karl Olson
  - Prashant Shenoy
  - Paulo Tabuada
  - Gunjan Verma
links:
  - https://anrg.usc.edu/www/papers/iobt_network_synthesis.pdf
abstract: "We develop a network synthesis scenario, which is built around a concrete perimeter surveillance application, yet we believe captures a number of the challenges and requirements that are common to other tactical communication and computational network applications. The proposed scenario addresses the problem of binary population identification within a perimeter: our goal is to synthesize a sensing and computing network that classifies people moving within a given perimeter to one of two categories (e.g., friend or foe). We discuss several open challenges that we organize across the following clusters: sensor placement, communication network provisioning and optimization, computational task placement, dynamic resynthesis and resilience under adversarial settings. We also briefly discuss approaches that attempt to address such challenges."
tags:
  - distributed-computing
  - internet-of-things

Network Synthesis for Tactical Environments: Scenario, Challenges, and Opportunities

Tzanis Anevlavis, Jonathan Bunton, Jared Coleman, Mine Dogan, Eugenio Grippo, Abel Souza, Christina Fragouli, Bhaskar Krishnamachari, Matthew Maness, Karl Olson, Prashant Shenoy, Paulo Tabuada, Gunjan Verma

SPIE Defense + Commercial Sensing · June 6, 2022 · doi:10.1117/12.2619048 · PDF

Abstract

We develop a network synthesis scenario, which is built around a concrete perimeter surveillance application, yet we believe captures a number of the challenges and requirements that are common to other tactical communication and computational network applications. The proposed scenario addresses the problem of binary population identification within a perimeter: our goal is to synthesize a sensing and computing network that classifies people moving within a given perimeter to one of two categories (e.g., friend or foe). We discuss several open challenges that we organize across the following clusters: sensor placement, communication network provisioning and optimization, computational task placement, dynamic resynthesis and resilience under adversarial settings. We also briefly discuss approaches that attempt to address such challenges.

Created · Updated