D3.1 – Mobility Data Processing at the Computing Continuum

The goal of this deliverable is to present the 1st version of the Mobility Data Processing at the Computing Continuum services, hereafter called ‘emeralds’, that are being developed under Work Package 3. As its title suggests, the objective of this WP is to develop mobility processing modules that are built for the Computing continuum (CC). The CC spans a wide range of devices that can be deployed in various conditions, with some tailored for centralized compute and some for decentralized in-situ processing. The distinction between the two mostly revolves around energy usage (which directly correlates with compute capability, size etc.), because devices that are highly capable require much more energy and space, meaning that they are not easily deployable and horizontally scalable. However, compute nodes that tend to use less power are often cheaper and smaller, meaning that they are easily configurable to accommodate a wide range of scenarios through their multi location installation. This allows for in-situ data processing, greatly reducing latency and response times when the underlying computation can be effectively performed by such nodes meeting the advanced needs of modern mobility data analytics applications. This deliverable presents seven (7) emeralds that are developed under the three WP3 tasks. The work covered in this deliverable is organized according to the designated computing tier supported by each component, with emeralds from T3.1 focusing on Edge/Fog applications and emeralds from T3.2 and T3.3 primarily utilizing the Fog/Cloud. The emeralds code releases are provided as software repositories with release notes and instructions on executing the developed methods. This report accompanies the emeralds code releases. The key aspects covered in this report include thorough descriptions of the emeralds and how they advance the state of the art, both with respect to the mobility data science field as well as the achieved and targeted performance and overall improvements related to the state-of-the-art, reflected by the scientific/technical KPIs. Validation and demonstration of the WP3 tools will be performed and reported within the respective WP5 use cases.