| Abstract |
In the Smart Cities context, a plethora of Middle ware Platforms had been proposed to support applications execution and data processing. Despite all the progress already made, the vast majority of solutions have not met the requirements of Applications' Runtime, Development, and Deployment when related to Scalability. Some studies point out that just 1 of 97 (1%) reported platforms reach this all this set of requirements at same time. This small number of platforms may be explained by some reasons: i) Big Data: The huge amount of processed and stored data with various data sources and data types, ii) Multi domains: many domains involved (Economy, Traffic, Health, Security, Agronomy, etc.), iii) Multiple processing methods like Data Flow, Batch Processing, Services, and Microservices, and 4) High Distributed Degree: The use of multiple IoT and BigData tools combined with execution at various computational levels (Edge, Fog, Cloud) leads applications to present a high level of distribution. Aware of those great challenges, we propose Sapparchi, an integrated architectural model for Smart Cities applications that defines multi-processing levels (Edge, Fog, and Cloud). Also, it presents the Sapparchi middleware platform for developing, deploying, and running applications in the smart city environment with an osmotic multi-processing approach that scales applications from Cloud to Edge. Finally, an experimental evaluation exposes the main advantages of adopting Sapparchi. |