Advisor: Dr. Mukhopadhyay
164B Coates Hall
Louisiana State University
Baton Rouge, LA 70803
Phone: 225 578 2819
Distributed Datastores, Big Data Analytics, Large Scale Parallel Processing
Explore the possibility of flexibility in providing strong consistency in storage systems wherein it can be enforced without harming availability and failure tolerance beyond an acceptable threshold; at other times this system is allowed to fall back on weaker models of consistency.
An adaptive situation aware multi-agent framework based on a new learning architecture called agile machine learning.
An automatic elastic scaling system for cloud resources that dynamically adds or removes instances with change of workload at the same time optimising the cost.
Text Mining on Emails to identify keywords.
OptCon: a Flexible Workload and SLA-Aware Framework for Consistency Tuning.
Consistify: A Framework for Safe and Fair Execution of Concurrent SLA-driven Client Applications on Quorum-based Datastores.
OptEx: A Deadline-Aware Cost Optimization Model for Spark.
Kaliappa Ravindran, Supratik Mukhopadhyay, Subhajit Sidhanta, and Ali Sabbir, Managing Shared Contexts in Distributed Multi-player Game Systems, COMSNETS, 2014
Subhajit Sidhanta and Supratik Mukhopadhyay, An Ad-hoc Distributed Execution Environment for Multi-Agent Systems, COMSNETS, 2013
Subhajit Sidhanta and Supratik Mukhopadhyay, Managing A Cloud for Multi-agent Systems on Ad-hoc Networks, 5th IEEE International Conference on Cloud Computing (CLOUD), 2012
Subhajit Sidhanta, Wojciech Golab, Supratik Mukhopadhyay, OptEx: A Deadline-Aware Cost Optimization Model for Spark, 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2016
Subhajit Sidhanta, Wojciech Golab, Supratik Mukhopadhyay, Saikat Basu, OptCon: An Adaptable SLA-Aware Consistency Tuning Framework for Quorum-based Stores, 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2016.