Applying reinforcement learning towards automating resource allocation and application scalability in the cloud E Barrett, E Howley, J Duggan Concurrency and computation: practice and experience 25 (12), 1656-1674, 2013 | 291 | 2013 |
Autonomous hvac control, a reinforcement learning approach E Barrett, S Linder Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 149 | 2015 |
Deep reinforcement learning for home energy management system control P Lissa, C Deane, M Schukat, F Seri, M Keane, E Barrett Energy and AI 3, 100043, 2021 | 122 | 2021 |
Predicting host CPU utilization in the cloud using evolutionary neural networks K Mason, M Duggan, E Barrett, J Duggan, E Howley Future Generation Computer Systems 86, 162-173, 2018 | 114 | 2018 |
CPU workload forecasting of machines in data centers using LSTM recurrent neural networks and ARIMA models D Janardhanan, E Barrett 2017 12th international conference for internet technology and secured …, 2017 | 104 | 2017 |
Predicting host CPU utilization in cloud computing using recurrent neural networks M Duggan, K Mason, J Duggan, E Howley, E Barrett 2017 12th international conference for internet technology and secured …, 2017 | 99 | 2017 |
A learning architecture for scheduling workflow applications in the cloud E Barrett, E Howley, J Duggan 2011 IEEE ninth European conference on web services, 83-90, 2011 | 85 | 2011 |
A review of behind-the-meter energy storage systems in smart grids M Rezaeimozafar, RFD Monaghan, E Barrett, M Duffy Renewable and Sustainable Energy Reviews 164, 112573, 2022 | 69 | 2022 |
Applying reinforcement learning towards automating energy efficient virtual machine consolidation in cloud data centers R Shaw, E Howley, E Barrett Information Systems 107, 101722, 2022 | 69 | 2022 |
An energy efficient anti-correlated virtual machine placement algorithm using resource usage predictions R Shaw, E Howley, E Barrett Simulation Modelling Practice and Theory 93, 322-342, 2019 | 63 | 2019 |
Method to use augumented reality to function as hmi display RM Fallon, P Bohan, E Barrett, SP Katru, V Rathish, VM Deokar US Patent App. 14/480,862, 2016 | 62 | 2016 |
An advanced reinforcement learning approach for energy-aware virtual machine consolidation in cloud data centers R Shaw, E Howley, E Barrett 2017 12th International Conference for Internet Technology and Secured …, 2017 | 54 | 2017 |
A multitime‐steps‐ahead prediction approach for scheduling live migration in cloud data centers M Duggan, R Shaw, J Duggan, E Howley, E Barrett Software: Practice and Experience 49 (4), 617-639, 2019 | 45 | 2019 |
A reinforcement learning approach for dynamic selection of virtual machines in cloud data centres M Duggan, K Flesk, J Duggan, E Howley, E Barrett 2016 sixth international conference on innovative computing technology …, 2016 | 44 | 2016 |
A network aware approach for the scheduling of virtual machine migration during peak loads M Duggan, J Duggan, E Howley, E Barrett Cluster Computing 20, 2083-2094, 2017 | 41 | 2017 |
A reinforcement learning approach for the scheduling of live migration from under utilised hosts M Duggan, J Duggan, E Howley, E Barrett Memetic Computing 9, 283-293, 2017 | 40 | 2017 |
Serverless computing: Behind the scenes of major platforms D Kelly, F Glavin, E Barrett 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), 304-312, 2020 | 38 | 2020 |
Using reinforcement learning to conceal honeypot functionality S Dowling, M Schukat, E Barrett Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 35 | 2019 |
Improving adaptive honeypot functionality with efficient reinforcement learning parameters for automated malware S Dowling, M Schukat, E Barrett Journal of Cyber Security Technology 2 (2), 75-91, 2018 | 32 | 2018 |
An autonomous network aware vm migration strategy in cloud data centres M Duggan, J Duggan, E Howley, E Barrett 2016 International Conference on Cloud and Autonomic Computing (ICCAC), 24-32, 2016 | 32 | 2016 |