activity
20172022
most citedMonotonic Filtering for Distributed Collection

1 citations · 2 across the 2 of their papers we have counts for

collaborators

6 papers

cs.SE20221 cited

Aggregate Processes as Distributed Adaptive Services for the Industrial Internet of Things

Lorenzo Testa, Giorgio Audrito, Ferruccio Damiani +1

The Industrial Internet of Things (IIoT) promises to bring many benefits, including increased productivity, reduced costs, and increased safety to new generation manufacturing plan…

cs.DC20211 cited

Monotonic Filtering for Distributed Collection

Hunza Zainab, Giorgio Audrito, Soura Dasgupta +1

Distributed data collection is a fundamental task in open systems. In such networks, data is aggregated across a network to produce a single aggregated result at a source device. T…

cs.SE2019

On Distributed Runtime Verification by Aggregate Computing

Giorgio Audrito, Ferruccio Damiani, Volker Stolz +1

Runtime verification is a computing analysis paradigm based on observing a system at runtime (to check its expected behaviour) by means of monitors generated from formal specificat…

cs.DC2018

Resilient Blocks for Summarising Distributed Data

Giorgio Audrito, Sergio Bergamini

Summarising distributed data is a central routine for parallel programming, lying at the core of widely used frameworks such as the map/reduce paradigm. In the IoT context it is ev…

cs.DC2018

Aggregate Graph Statistics

Giorgio Audrito, Ferruccio Damiani, Mirko Viroli

Collecting statistic from graph-based data is an increasingly studied topic in the data mining community. We argue that these statistics have great value as well in dynamic IoT con…

cs.DC2017

Engineering Resilient Collective Adaptive Systems by Self-Stabilisation

Mirko Viroli, Giorgio Audrito, Jacob Beal +2

Collective adaptive systems are an emerging class of networked computational systems, particularly suited in application domains such as smart cities, complex sensor networks, and…