Current Research

Ongoing Research

Published more than 50 research articles in various reputed journals and international conferences. My research interests cover cognitive radio networks, wireless communications, smart city, signal processing and deep learning.

Cluster-based MAC Protocol Design for Cognitive Radio Ad-hoc Network

With the swift expansion of wireless technologies, demand for radio spectrum is continuously mounting. Cognitive radio practices an open spectrum allocation technique, which can ensure efficient handling of the frequency bands. This project aims to develop an efficient cluster model for cognitive radio ad-hoc networks. The clustering scheme anticipates to maintain set of free common channels in every cluster, which allows smooth shifting among control channels.

On-Demand Routing Protocol for Cluster-Based Cognitive Radio Ad-Hoc Network

An on-demand routing protocol for cluster-based cognitive radio ad-hoc network is focused in the project. In this routing protocol, relaying nodes are the cluster-heads and the forwarding nodes. Moreover, the routing protocol is defined as a weighted graph problem, where delay has been considered as the performance metric of the routing protocol. To calculate the weight of a link, three types of delay are considered, namely switching delay, back-off delay and queuing delay. Thus, to ensure faster data delivery to the destination, the proposed protocol selects the routing path that provides the least cumulative link weights.

Vehicle-2-Vehicle MAC Protocol for CR-VANET

It is anticipated that CR-enabled vehicular network (CR-V ANET) enriches communication efficiency on existing vehicular networks (VANETs). This project fovuses to develop a vehicle-2-vehicle MAC protocol for CR-VANET in multu-obj A framework for multi-agent based intelligent traffic system is also highlighted in the project.

Sensor Search Algorithms for Sensing as a Service for The Internet of Things

The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This research plans for a context-aware sensor search, selection and ranking model.