Lambda architecture for cost-effective batch and speed big data processing M Kiran, P Murphy, I Monga, J Dugan, SS Baveja 2015 IEEE international conference on big data (big data), 2785-2792, 2015 | 345 | 2015 |
FLAME: simulating large populations of agents on parallel hardware architectures M Kiran, P Richmond, M Holcombe, LS Chin, D Worth, C Greenough Proceedings of the 9th International Conference on Autonomous Agents and …, 2010 | 140 | 2010 |
Modelling complex biological systems using an agent-based approach M Holcombe, S Adra, M Bicak, S Chin, S Coakley, AI Graham, J Green, ... Integrative Biology 4 (1), 53-64, 2012 | 90 | 2012 |
Security risks and their management in cloud computing AU Khan, M Oriol, M Kiran, M Jiang, K Djemame 4th IEEE International Conference on Cloud Computing Technology and Science …, 2012 | 75 | 2012 |
Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency S Touzani, AK Prakash, Z Wang, S Agarwal, M Pritoni, M Kiran, R Brown, ... Applied Energy 304, 117733, 2021 | 73 | 2021 |
A risk assessment framework and software toolkit for cloud service ecosystems K Djemame, D Armstrong, M Kiran, M Jiang Cloud computing 5, 119-126, 2011 | 68 | 2011 |
Enabling intent to configure scientific networks for high performance demands M Kiran, E Pouyoul, A Mercian, B Tierney, C Guok, I Monga Future Generation Computer Systems 79, 205-214, 2018 | 65 | 2018 |
Failover strategy for fault tolerance in cloud computing environment B Mohammed, M Kiran, KM Maiyama, MM Kamala, IU Awan Software: Practice and Experience 47 (9), 1243-1274, 2017 | 55 | 2017 |
Large-scale modeling of economic systems M Holcombe, S Coakley, M Kiran, S Chin, C Greenough, D Worth, ... Complex Systems Publications, 2013 | 49 | 2013 |
Cross-facility science with the Superfacility Project at LBNL B Enders, D Bard, C Snavely, L Gerhardt, J Lee, B Totzke, K Antypas, ... 2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop …, 2020 | 44 | 2020 |
Levenberg–Marquardt multi-classification using hinge loss function BM Ozyildirim, M Kiran Neural Networks 143, 564-571, 2021 | 38 | 2021 |
A performance modeling framework for lambda architecture based applications M Gribaudo, M Iacono, M Kiran Future Generation Computer Systems 86, 1032-1041, 2018 | 38 | 2018 |
Hyperparameter tuning for deep reinforcement learning applications M Kiran, M Ozyildirim arXiv preprint arXiv:2201.11182, 2022 | 36 | 2022 |
Towards a service lifecycle based methodology for risk assessment in cloud computing M Kiran, M Jiang, DJ Armstrong, K Djemame 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure …, 2011 | 35 | 2011 |
Biological synthesis of silver nanoparticles from marine alga Colpomenia sinuosa and its in vitro anti-diabetic activity DVK Manam, S Murugesan American Journal of Bio-pharmacology Biochemistry and Life Sciences (AJBBL …, 2014 | 31 | 2014 |
Analysis of cloud test beds using opensource solutions B Mohammed, M Kiran 2015 3rd International Conference on Future Internet of Things and Cloud …, 2015 | 29 | 2015 |
Classifying elephant and mice flows in high-speed scientific networks A Chhabra, M Kiran Proc. INDIS, 1-8, 2017 | 28 | 2017 |
Validation and discovery from computational biology models M Kiran, S Coakley, N Walkinshaw, P McMinn, M Holcombe Biosystems 93 (1-2), 141-150, 2008 | 27 | 2008 |
Using machine learning for intent-based provisioning in high-speed science networks H Mahtout, M Kiran, A Mercian, B Mohammed Proceedings of the 3rd international workshop on systems and network …, 2020 | 26 | 2020 |
Optimising fault tolerance in real-time cloud computing IaaS environment B Mohammed, M Kiran, IU Awan, KM Maiyama 2016 IEEE 4th international conference on future internet of things and …, 2016 | 26 | 2016 |