A Phenomic Algorithm for Inference of Gene Networks Using S-Systems and Memetic Search. - Rio G. L. D'Souza; K. Chandrasekaran 001; A. Kandasamy (BIONETICS, 2010)

A Multiobjective Phenomic Algorithm for Inference of Gene Networks. - Rio G. L. D'Souza; K. Chandrasekaran 001; A. Kandasamy (BIONETICS, 2010)

A Phenomic Approach to Genetic Algorithms for Reconstruction of Gene Networks. - Rio G. L. D'Souza; K. Chandrasekaran 001; A. Kandasamy (IC3 (1), 2010)

Inference of Gene Networks from Microarray Data through a Phenomic Approach. - Rio G. L. D'Souza; K. Chandrasekaran 001; A. Kandasamy (ICT, 2010)

Improved NSGA-II Based on a Novel Ranking Scheme - Rio G. L. D'Souza; K. Chandrasekaran 001; A. Kandasamy (CoRR, 2010)

Node - Link Disjoint Multipath Routing Protocols for Wireless Sensor Networks - A Survey and Conceptual Modeling. - Muni Venkateswarlu K.; K. Chandrasekaran 001; A. Kandasamy (ADCONS, 2011)

Energy-efficient edge-based network partitioning scheme for wireless sensor networks. - Muni Venkateswarlu K.; A. Kandasamy; K. Chandrasekaran 001 (ICACCI, 2013)

An Energy-Efficient Hybrid Clustering Mechanism for Wireless Sensor Network. - Muni Venkateswarlu K.; A. Kandasamy; K. Chandrasekaran 001 (Unmanned Syst., 2015)

Survey on meta heuristic optimization techniques in cloud computing. - S. R. Shishira; A. Kandasamy; K. Chandrasekaran 001 (ICACCI, 2016)

Workload Characterization: Survey of Current Approaches and Research Challenges. - S. R. Shishira; A. Kandasamy; K. Chandrasekaran 001 (ICCCT, 2017)

Multi-layer multi-level color distribution - User feedback model with wavelet analysis for color image retrieval. - A. Kandasamy; M. Sundaram (Comput. Electr. Eng., 2018)

Exploring the support for high performance applications in the container runtime environment. - John Paul Martin; A. Kandasamy; K. Chandrasekaran 001 (Hum. centric Comput. Inf. Sci., 2018)

Fuzzy Reinforcement Learning based Microservice Allocation in Cloud Computing Environments. - Christina Terese Joseph; John Paul Martin; K. Chandrasekaran 001; A. Kandasamy (TENCON, 2019)

Elucidating the challenges for the praxis of fog computing: An aspect-based study. - John Paul Martin; A. Kandasamy; K. Chandrasekaran 001; Christina Terese Joseph (Int. J. Commun. Syst., 2019)

Mobility aware autonomic approach for the migration of application modules in fog computing environment. - John Paul Martin; A. Kandasamy; K. Chandrasekaran 001 (J. Ambient Intell. Humaniz. Comput., 2020)

CREW: Cost and Reliability aware Eagle-Whale optimiser for service placement in Fog. - John Paul Martin; A. Kandasamy; K. Chandrasekaran 001 (Softw. Pract. Exp., 2020)

Machine Learning Powered Autoscaling for Blockchain-Based Fog Environments. - John Paul Martin; Christina Terese Joseph; K. Chandrasekaran 001; A. Kandasamy (BLOCKCHAIN, 2021)

BeeM-NN: An efficient workload optimization using Bee Mutation Neural Network in federated cloud environment. - S. R. Shishira; A. Kandasamy (J. Ambient Intell. Humaniz. Comput., 2021)

A Novel Feature Extraction Model for Large-Scale Workload Prediction in Cloud Environment. - S. R. Shishira; A. Kandasamy (SN Comput. Sci., 2021)

Ontology for Contextual Fake News Assessment Based on Text and Images. - K. Chandrasekaran 001; A. Kandasamy; Venkatesan M; Prabhavathi P; M. Gokuldhev; Aishwarya C (PDP, 2024)