John Paul Martin

According to our database, John Paul Martin authored at least 11 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Fog Assisted Personalized Dynamic Pricing for Smartgrid.

Christina Terese Joseph, John Paul Martin, K. Chandrasekaran, S. P. Raja

IEEE Trans. Comput. Soc. Syst., December, 2023

Improving Industry 4.0 Readiness: Monolith Application Refactoring using Graph Attention Networks.

Tanisha Rathod, Christina Terese Joseph, John Paul Martin

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2021

Machine Learning Powered Autoscaling for Blockchain-Based Fog Environments.

John Paul Martin, Christina Terese Joseph, K. Chandrasekaran, A. Kandasamy

Proceedings of the Blockchain and Applications - 3rd International Congress, 2021

2020

CREW: Cost and Reliability aware Eagle-Whale optimiser for service placement in Fog.

John Paul Martin, A. Kandasamy, K. Chandrasekaran

Softw. Pract. Exp., 2020

Mobility aware autonomic approach for the migration of application modules in fog computing environment.

John Paul Martin, A. Kandasamy, K. Chandrasekaran

J. Ambient Intell. Humaniz. Comput., 2020

HTmRPL++ : A Trust-Aware RPL Routing Protocol for Fog Enabled Internet of Things.

Nishanth Subramanian, Shashwatha Mitra G. B, John Paul Martin, K. Chandra Sekaran

Proceedings of the 2020 International Conference on COMmunication Systems & NETworkS, 2020

2019

Elucidating the challenges for the praxis of fog computing: An aspect-based study.

John Paul Martin, A. Kandasamy, K. Chandrasekaran, Christina Terese Joseph

Int. J. Commun. Syst., 2019

Location Privacy Using Data Obfuscation in Fog Computing.

Chandan Naik, M. Siddhartha, John Paul Martin, K. Chandrasekaran

Proceedings of the TENCON 2019, 2019

Fuzzy Reinforcement Learning based Microservice Allocation in Cloud Computing Environments.

Christina Terese Joseph, John Paul Martin, K. Chandrasekaran, A. Kandasamy

Proceedings of the TENCON 2019, 2019

2018

Exploring the support for high performance applications in the container runtime environment.

John Paul Martin, A. Kandasamy, K. Chandrasekaran

Hum. centric Comput. Inf. Sci., 2018

Machine Learning Approaches for Resource Allocation in the Cloud: Critical Reflections.

Akarsh Murali, Nibir Nirjas Das, Shiv Shankar Sukumaran, K. Chandrasekaran, Christina Terese Joseph, John Paul Martin

Proceedings of the 2018 International Conference on Advances in Computing, 2018