5 papers · 1 filter
OrchNAS: Orchestrated Neural Architecture Search Service for Personalised Federated Edge Intelligence
Keya Patel, Sajib Mistry, Sheik Mohammad Mostakim Fattah +1
We propose OrchNAS, an energy-aware, personalised, federated edge intelligence framework that leverages a Neural Architecture Search Service to automatically design service-adaptiv…
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…
Reinforcement Learning Controlled Adaptive PSO for Task Offloading in IIoT Edge Computing
Minod Perera, Sheik Mohammad Mostakim Fattah, Sajib Mistry +1
Industrial Internet of Things (IIoT) applications demand efficient task offloading to handle heavy data loads with minimal latency. Mobile Edge Computing (MEC) brings computation c…