Abstract

As the Internet-of-Vehicles (IoV) technology becomes an increasingly important trend for future transportation, de-signing large-scale IoV systems has become a critical task that aims to process big data uploaded by fleet vehicles and to provide data-driven services. The IoV data, especially high-frequency vehicle statuses (e.g., location, engine parameters), are characterized as large volume with a low density of value and low data quality. Such characteristics pose challenges for developing real-time applications based on such data. In this paper, we address the challenges in de-signing a scalable IoV system by describing CarStream, an industrial system of big data processing for chauffeured car services. Photon is deployed within Google Advertising System to join data streams such as web search queries and user clicks on advertisements. It produces joined logs that are used to derive key business metrics, including billing for advertisers. Our production deployment processes millions of events per minute at peak with an average end-to-end latency of less than 10 seconds. We also present challenges and solutions in maintaining large persistent state across geographically distant locations, and highlight the design principles that emerged from our experience. Rakshitha K. S | Radhika K. R"CarStream: An Industrial System of Big Data Processing for Internet of Vehicles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14408.pdf http://www.ijtsrd.com/computer-science/database/14408/carstream-an-industrial-system-of-big-data-processing-for-internet-of-vehicles/rakshitha-k-s

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