Network Resilience

LNRA: LinQuest Network Resilience Algorithms

LinQuest has developed advanced, novel, and patent-pending Machine Learning algorithms to enable resilient operation of large-scale communication networks via alternative network pathways during Radio Frequency (RF) jamming, spectrum congestion, or cyber attack.

Features and
Benefits

Features

LinQuest’s Network Resilience Algorithms:

  • Are encapsulated in software code that can be deployed within a networked system – at either the node level or a centralized compute location
  • Constantly monitor network nodes and links for congestion, quality, performance, cost, jamming, and other attributes
  • Detect performance degradation within a link, then re-route the data to links that are not affected to provide assured delivery of data from a source to a target
  • Recommend network configurations to optimize resilience
  • Analyze, characterize, and predict adversary attacks using AI/ML techniques even if adversary attacks are AI/ML-driven
  • Can be implemented on emulated custom networks in a Resiliency Test Bed within LinQuest’s state-of-the-art LinQlab

Benefits

  • Can be implemented on emulated custom networks in a Resiliency Test Bed within LinQuest’s state-of-the-art LinQlab
  • Faster resumption of full network capacity after disruption/attack
  • Reduced cost of response to disruption/attack through automated recovery
  • Broad applicability across network acquisition and operations phases