Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 3-26-2020 Relational Database Design and Multi-Objective Database Queries for Position Navigation and Timing Data Sean A. Mochocki Follow this and additional works at: https://scholar.afit.edu/etd Part of the Databases and Information Systems Commons, and the Navigation, Guidance, Control and Dynamics Commons Recommended Citation Mochocki, Sean A., "Relational Database Design and Multi-Objective Database Queries for Position Navigation and Timing Data" (2020). Theses and Dissertations. 3184. https://scholar.afit.edu/etd/3184 This Thesis is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. RELATIONAL DATABASE DESIGN AND MULTI-OBJECTIVE DATABASE QUERIES FOR POSITION NAVIGATION AND TIMING DATA THESIS Sean A. Mochocki, Captain, USAF AFIT-ENG-MS-20-M-045 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. The views expressed in this document are those of the author and do not reflect the official policy or position of the United States Air Force, the United States Department of Defense or the United States Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENG-MS-20-M-045 RELATIONAL DATABASE DESIGN AND MULTI-OBJECTIVE DATABASE QUERIES FOR POSITION NAVIGATION AND TIMING DATA THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science Sean A. Mochocki, B.S.E.E., B.S.M.E. Captain, USAF March 2020 DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENG-MS-20-M-045 RELATIONAL DATABASE DESIGN AND MULTI-OBJECTIVE DATABASE QUERIES FOR POSITION NAVIGATION AND TIMING DATA THESIS Sean A. Mochocki, B.S.E.E., B.S.M.E. Captain, USAF Committee Membership: Robert C Leishman, Ph.D. Chair Kyle J Kauffman, Ph.D. Member John F Raquet, Ph.D. Member AFIT-ENG-MS-20-M-045 Abstract Performing flight tests is a natural part of researching cutting edge sensors and filters for sensor integration. Unfortunately, tests are expensive, and typically take many months of planning. A sensible goal would be to make previously collected data readily available to researchers for future development. The Air Force Institute of Technology (AFIT) has hundreds of data logs poten- tially available to aid in facilitating further research in the area of navigation. A database would provide a common location where older and newer data sets are available. Such a database must be able to store the sensor data, metadata about the sensors, and affiliated metadata of interest. This thesis proposes a standard approach for sensor and metadata schema and three different design approaches that organize this data in relational databases. Queries proposed by members of the Autonomy and Navigation Technology (ANT) Center at AFIT are the foundation of experiments for testing. These tests fall into two categories, downloaded data, and queries which return a list of missions. Test databases of 100 and 1000 missions are created for the three design approaches to simulate AFIT's present and future volume of data logs. After testing, this thesis recommends one specific approach to the ANT Center as its database solution. In order to enable more complex queries, a Genetic algorithm and Hill Climber algorithm are developed as solutions to queries in the combined Knapsack/Set Cov- ering Problem Domains. These algorithms are tested against the two test databases for the recommended database approach. Each algorithm returned solutions in under two minutes, and may be a valuable tool for researchers when the database becomes operational. iv Table of Contents Page Abstract . iv List of Figures . viii List of Tables . xi List of Acronyms . xiv I. Introduction . 1 1.1 Background and Motivation . 1 1.2 Problem Background. 2 1.3 Design Objectives and Characteristics . 2 II. Background and Related Work . 4 2.1 Overview . 4 2.2 Position Navigation and Timing Data . 4 2.2.1 Scorpion Data Model . 5 2.2.2 YAML Ain't Markup Language . 6 2.2.3 Lightweight Communications and Marshalling . 6 2.3 Big Data Overview . 7 2.3.1 Definitions of Big Data . 8 2.3.2 Five V Model . 9 2.4 Data Modeling . 12 2.5 Relational Databases . 14 2.5.1 Normalization . 15 2.5.2 Entity Relationship Diagrams . 16 2.5.3 Structured Query Language . 17 2.5.4 SQLite . 18 2.5.5 PostgreSQL . 18 2.6 Non-Relational Databases . 18 2.6.1 The Consistent, Available, or Partition Tolerant Theorem . 19 2.6.2 Basically Available, Soft state, Eventual consistency Properties. 21 2.6.3 Standard Types of Not only SQL Databases. 22 2.7 Data Warehouses, OLTPs and OLAPs . 24 2.8 NewSQL . 25 2.9 Multi-Objective Database Queries . 26 2.10 Cloud Computing . 27 2.11 Relevant Research . 28 v Page 2.12 Summary . 29 III. Design............................................................32 3.1 ION/PLANS Paper Introduction . 32 3.2 Relevant Background . 33 3.2.1 PNT Database Characteristics . 34 3.2.2 Relational Databases . 35 3.2.3 Non-Relational Databases . 37 3.2.4 Database Decision Summary . 39 3.3 Database Designs. 40 3.3.1 Requirements and Approaches . 40 3.3.2 Table and Relationship Descriptions . 41 3.4 Design of Experiments . 48 3.4.1 Database Population . 48 3.4.2 Test Designs . 49 3.4.3 Expected Performance . 53 3.4.4 Test Procedures . 53 3.5 Test Results . 55 3.5.1 Download Test Results Summary . 55 3.5.2 SDM Query Test Results Summary . 57 3.6 Conclusion . 61 3.7 Database Population . 63 3.7.1 Log File Ordering . 63 3.7.2 Non-Sensor Metadata Insertion Algorithms . 64 3.7.3 insertChannelInformation Function . 65 3.7.4 insertRandomSensorMetadata . 66 3.7.5 insertSDMData . 68 3.8 Indexes . 72 3.9 Removed Metadata Query Test Figures. 73 IV. Experimental Scenarios . 76 4.1 Journal Of Evolutionary Computation Paper . 76 4.2 Background and Related Queries . 78 4.3 Problem Domain . 83 4.3.1 Set Covering Problem . 83 4.3.2 The Knapsack Problem . 84 4.3.3 Combined Problem . 85 4.4 Stochastic Algorithms for the Combined MO KP/SCP . 88 4.4.1 Genetic Algorithm . ..