Planning Big-Data Distributed Processing for Combat ID
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Authors
Rowe, Neil C.
Allen, Bruce D.
Sollish, Andrew
Zhou, James
Subjects
combat identification
aircraft
ships
big data
distributed processing
anomalies
aircraft
ships
big data
distributed processing
anomalies
Advisors
Date of Issue
2018-04
Date
Presented April 10-12, 2018
Period of Performance: 10/01/2018-9/30/18
Period of Performance: 10/01/2018-9/30/18
Publisher
Monterey, California: Naval Postgraduate School
Language
en_US
Abstract
Project Summary: Combat identification (Combat ID) of aircraft and ships is an important problem for militaries. Aircraft in particular move quickly, may not aid identification, may be subject to system malfunctions, or may be misconfigured. Identification is also becoming more difficult because commercial vehicles are less often in air lanes, and we now have autonomous aircraft in the air on nonstandard routes. We now have basic information about most major aircraft from satellite coverage, so combat identification today is a big-data problem. Even if we have facilities to handle large amounts of data, often we have a limited bandwidth to transmit sensor data to them. Our strategy is to push some of the processing and intelligence "to the edge" or to the platforms that collect data. We are developing methods whereby important data can be identified at an early stage. We have identified 16 factors which should be reported when they have anomalous values such as speeds, altitudes, counts in particular areas, deviations from tracks, and mixes of aircraft types in an area. Full data will still need to be transmitted eventually, but early forwarding of time-critical information could help neighboring platforms if we can identify it. We show some results from a prototype implementation using a sample of 110 million records from the ADS-B database. Results on a Hadoop distributed-processing system show speedups of 2-70 over a single-processor implementation depending on the subtask, which says this problem is well suited for distributed big-data methods.
Type
Report
Description
NPS NRP Executive Summary
Series/Report No
Department
Computer Science (CS)
Organization
Naval Research Program
Identifiers
NPS Report Number
NPS-18-N193-B
Sponsors
N2/N6 - Information Warfare
Funder
NPS-18-N193-B
Format
3 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.