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Using Polygot Persistence with NoSQL Databases for Streaming Multimedia, Sensor, and Messaging Services in Autonomous Vehicles
Technical Paper
2020-01-0942
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs. NoSQL databases such as Graph databases support big data necessary for the demands of modern software development. Graph databases can scale AV data by using geospatial and geolocation coordinates as entities for flexible queries and pattern recognition. This paper addresses the development of an autonomous platform to process structured, unstructured, semi-structured, and polymorphic data using NoSQL databases built on a hybrid framework. Using Polygot Persistence for processing multimedia, social media, GPS data, audio, fleet diagnostics, and messaging services will be incorporated into the Platform as a Services (PaaS). Integration of NoSQL’s toolboxes and horizontal scalability through cloud deployments will continue the development of an integrated database that’s scalable for the PaaS application.
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Brown, K., "Using Polygot Persistence with NoSQL Databases for Streaming Multimedia, Sensor, and Messaging Services in Autonomous Vehicles," SAE Technical Paper 2020-01-0942, 2020, https://doi.org/10.4271/2020-01-0942.Data Sets - Support Documents
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