Talks

Conference on Parallel, Distributed, and Network-Based Processing (PDP 2020)

In the last years, the ability to produce and gather data has exponentially increased. In the Internet of Things’ era, huge amount of digital data is generated and collected from various sources, such as sensors, cameras, mobile devices, GPS devices, web applications and services, which must be acquired, pre-processed and analyzed in real-time through a large set of computing and storage nodes. Examples of systems are social media platforms that analyse concurrently various patterns and trends related to human behaviours, driver-less vehicles that receive information from a very large number of sensors and need to make immediate decisions, or medical imaging applications that continuously analyse different types of images to provide unique and complementary information to the medical professionals. This presentation shows the way to approach the problem of the large-scale monitoring by the introducing a mathematical model for the optimized assignment of monitoring agents and aggregators, that reduces the transfer time of the raw monitoring data, while meeting strict I/O limitations.