31 citations · 84 across the 12 of their papers we have counts for
14 papers
Graph Neural Networks: Methods, Applications, and Opportunities
Lilapati Waikhom, Ripon Patgiri
In the last decade or so, we have witnessed deep learning reinvigorating the machine learning field. It has solved many problems in the domains of computer vision, speech recogniti…
A Review on Edge Analytics: Issues, Challenges, Opportunities, Promises, Future Directions, and Applications
Sabuzima Nayak, Ripon Patgiri, Lilapati Waikhom +1
Edge technology aims to bring Cloud resources (specifically, the compute, storage, and network) to the closed proximity of the Edge devices, i.e., smart devices where the data are…
countBF: A General-purpose High Accuracy and Space Efficient Counting Bloom Filter
Sabuzima Nayak, Ripon Patgiri
Bloom Filter is a probabilistic data structure for the membership query, and it has been intensely experimented in various fields to reduce memory consumption and enhance a system'…
RobustBF: A High Accuracy and Memory Efficient 2D Bloom Filter
Sabuzima Nayak, Ripon Patgiri
Bloom Filter is an important probabilistic data structure to reduce memory consumption for membership filters. It is applied in diverse domains such as Computer Networking, Network…
A Survey on Large Scale Metadata Server for Big Data Storage
Ripon Patgiri, Sabuzima Nayak
Big Data is defined as high volume of variety of data with an exponential data growth rate. Data are amalgamated to generate revenue, which results a large data silo. Data are the…
Big Computing: Where are we heading?
Sabuzima Nayak, Ripon Patgiri, Thoudam Doren Singh
This paper presents the overview of the current trends of Big data against the computing scenario from different aspects. Some of the important aspect includes the Exascale, the co…