Address
CIT @ Purdue University
KNOY 213, 401 N Grant St,
West Lafayette, IN 47909-2021
Get In Touch
nadig [AT] purdue [DOT] edu
Ph: +1.765.496.0873
Research Focus

Network Intelligence through Application-awareness.

What we do

Current Research Directions

01.

Cloud-native Infrastructure

Developing Edge/Cloud synergies for cloud-native networks with applications to 5G networks, multi-access edge and data-intensive science.

03.

AI/ML for Softwarized Networks

Approaches combining application-awareness, machine learning and data analytics for managing SDN-based cyberinfrastructures.

05.

Cloud Function Accelerators

Novel solutions to optimize cloud hyperscaler efficiencies using function accelerators for network and data processing tasks.

02.

Softwarized/Virtual Networks

Research focusing on SDN for network management, monitoring and differentiated services of data-intensive networks.

04.

Programmable Data Planes

Exploring programmable networks and data planes for in-network computing, policy enforcement, security and optimized traffic processing.

06.

Software-Defined Cybersecurity

Solutions for securing data-intensive networks using flexible, composable and virtualized network security architectures and frameworks.

Showcase

Our recent projects

Scalable Edge Computing

ERGO is an edge-computing architecture that is highly scalable, modular, and affords composability benefits to infrastructure-less Ag-IoT systems. Our implementation and evaluations show that ERGO can...

Application-Aware Load Balancing

APRIL is an application-aware, predictive and intelligent load balancing solution for data-intensive science.

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July 12, 2021

Scalable Edge Computing

ERGO is an edge-computing architecture that is highly scalable, modular, and affords composability benefits to infrastructure-less Ag-IoT systems. Our implementation and evaluations show that ERGO can...

  • Strategy

    Framework, Implementation

  • Design

    Prototype Cluster

  • Platforms

    Kubernetes, Prometheus

View Project
April 29, 2019

Application-Aware Load Balancing

APRIL is an application-aware, predictive and intelligent load balancing solution for data-intensive science.

  • Strategy

    Predictive Analytics

  • Design

    RNN-based Deep Neural Networks

  • Platforms

    Tensorflow, Elasticsearch

View Project