5 papers
Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments
Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +3
Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environments, widely adopted across hea…
Designing Sustainable Federated Learning as a Service using Neural Architecture Search
Keya Patel, Sajib Mistry, Sheik Fattah +4
The sustainability constraints of FLaaS consumers pose significant challenges to maintaining carbon-feasible federated training in FLaaS environments. These constraints often lead…
Test-Time Adaptive Composition for Machine Learning as a Service (MLaaS) in IoT Environments
Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +1
The dynamic nature of Internet of Things (IoT) environments affects the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions. Existing adaptive composition…
Machine Learning as a Service (MLaaS) Dataset Generator Framework for IoT Environments
Deepak Kanneganti, Sajib Mistry, Sheik Fattah +2
We propose a novel MLaaS Dataset Generator (MDG) framework that creates configurable and reproducible datasets for evaluating Machine Learning as a Service (MLaaS) selection and co…
Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments
Deepak Kanneganti, Sajib Mistry, Sheik Mohammad Mostakim Fattah +2
The dynamic nature of Internet of Things (IoT) environments challenges the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions. The uncertainty and variab…