1 citations · 1 across the 4 of their papers we have counts for
5 papers
Energy-Aware Two-Sided Learning for Dynamic Matching Games in Mobile Crowdsensing
Sumedh J. Dongare, Anja Klein, Andrea Ortiz
Mobile crowdsensing (MCS) is a promising enabler of Sensing-as-a-Service (SaaS) for next generation networks (NGNs), where sensing, communication, and computing are jointly conside…
Dynamic Hypergame for Task Assignment in Multi-platform Mobile Crowdsensing Under Incomplete Information
Sumedh J. Dongare, Christo Kurisummoottil Thomas, Andrea Ortiz +2
Mobile crowdsensing (MCS) is a promising distributed sensing paradigm for future wireless networks, where MCS platforms (MCSPs) recruit mobile units (MUs) through monetary incentiv…
Federated Reinforcement Learning for Efficient Mobile Crowdsensing under Incomplete Information
Sumedh J. Dongare, Patrick Weber, Andrea Ortiz +3
Mobile crowdsensing (MCS) is a distributed sensing architecture that utilizes existing sensors on mobile units (MUs) to perform sensing tasks. A mobile crowdsensing platform (MCSP)…
Deep Sleep Scheduling for Satellite IoT via Simulation Based Optimization
Wanja de Sombre, Monika Tomová, Marek Galinski +2
The Satellite Internet of Things (S-IoT) enables global connectivity for remote sensing devices that must operate energy-efficiently over long time spans. We consider an S-IoT syst…
The Best Time for an Update: Risk-Sensitive Minimization of Age-Based Metrics
Wanja de Sombre, Andrea Ortiz, Frank Aurzada +1
Popular methods to quantify transmitted data quality are the Age of Information (AoI), the Query Age of Information (QAoI), and the Age of Incorrect Information (AoII). We consider…