30 citations · 49 across the 9 of their papers we have counts for
10 papers
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'…
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…
A Review on Impact of Bloom Filter on Named Data Networking: The Future Internet Architecture
Sabuzima Nayak, Ripon Patgiri, Angana Borah
Today is the era of smart devices. Through the smart devices, people remain connected with systems across the globe even in mobile state. Hence, the current Internet is facing scal…
Shed More Light on Bloom Filter's Variants
Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain
Bloom Filter is a probabilistic membership data structure and it is excessively used data structure for membership query. Bloom Filter becomes the predominant data structure in app…