Decentralized Signal Processing and Distributed Control of Collaborative Autonomous Networks (17-ERD-101 LDRD Final Report)

Technical Report · Thu Oct 31 04:00:00 EDT 2019

DOI:https://doi.org/10.2172/1573142· OSTI ID:1573142

Goldhahn, Ryan A. ^[1]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Intelligent autonomous sensor networks, often comprised of large numbers of sensors, must be capable of jointly exploiting data collected at each agent in the network, and using that data to optimize their future actions towards multiple mission objectives. Centralized signal processing and optimization solutions process all data and determine all future actions at a single agent, and the resulting information and commands are disseminated back to the network. The communications bandwidth this requires and the single point of failure the central agent represents often make these solutions untenable for national security applications. In this project, several fundamental algorithms for solving both the decentralized signal processing and network optimization were developed, as well as simulation software to validate the results of these algorithms at scale. Specifically, novel algorithms for Bayesian decentralized estimation and decentralized detection and optimization based on the alternating direction method of multipliers (ADMM) were developed for autonomous sensor networks and published in the literature. The first large scale simulation of autonomous sensor networks (1000 agents) was conducted on this project, validating the performance of the developed algorithms. These algorithms and simulation tools are critical components of any decentralized autonomous network and have current and future national security applications, including distributed sensor networks for detection, estimation, and tracking problems, and large decentralized cyber-physical infrastructure such as the power grid.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 1573142
• Report Number(s): LLNL--TR-795739; 996995
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
97 MATHEMATICS AND COMPUTING