scispace - formally typeset
R

Rajashekhar C. Biradar

Researcher at Reva Institute of Technology and Management

Publications -  116
Citations -  2713

Rajashekhar C. Biradar is an academic researcher from Reva Institute of Technology and Management. The author has contributed to research in topics: Network packet & Wireless sensor network. The author has an hindex of 18, co-authored 102 publications receiving 2424 citations.

Papers
More filters
Proceedings ArticleDOI

A survey on routing protocols in Wireless Sensor Networks

TL;DR: A survey of state-of-the-art routing techniques in Wireless Sensor Networks (WSNs) and compares the routing protocols against parameters such as power consumption, scalability, mobility, optimal routing and data aggregation.
Journal ArticleDOI

Review: Review of multicast routing mechanisms in mobile ad hoc networks

TL;DR: This work provides an overview of existing multicast routing mechanisms based on routing categories that helps in multimedia communication over MANETs and point to directions for future research and development.
Journal ArticleDOI

A miniaturized metamaterial slot antenna for wireless applications

TL;DR: In this article, a novel miniaturized five band metamaterial inspired slot antenna is reported, which consists of a ring monopole and metamural Rectangular Complementary Split Ring Resonator (RCSRR) as the radiating part, two L and one T-shaped slot as the ground plane, respectively.
Journal ArticleDOI

A multiband reconfigurable slot antenna for wireless applications

TL;DR: In this article, a novel four band frequency reconfigurable antenna for 1.6, 2.5, 5.8, and 9.8 GHz frequency bands is presented, which has a compact size of 0.18 λ 0 × 0.
Journal ArticleDOI

Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach

TL;DR: This paper proposes a novel idea of an Active node based Fault Tolerance using Battery power and Interference model (AFTBI) in WSN to identify the faulty nodes using battery power model and interference model and found that AFTBI outperforms compared to the results of FDWSN.