3 papers
cs.NI2026
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…
cs.NI2026
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…
cs.LG2026
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)…