107 citations · 316 across the 21 of their papers we have counts for
21 papers
KmerCo: A lightweight K-mer counting technique with a tiny memory footprint
Sabuzima Nayak, Ripon Patgiri
K-mer counting is a requisite process for DNA assembly because it speeds up its overall process. The frequency of K-mers is used for estimating the parameters of DNA assembly, erro…
An Investigation on Learning, Polluting, and Unlearning the Spam Emails for Lifelong Learning
Nishchal Parne, Kyathi Puppaala, Nithish Bhupathi +1
Machine unlearning for security is studied in this context. Several spam email detection methods exist, each of which employs a different algorithm to detect undesired spam emails.…
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…
DeepBF: Malicious URL detection using Learned Bloom Filter and Evolutionary Deep Learning
Ripon Patgiri, Anupam Biswas, Sabuzima Nayak
Malicious URL detection is an emerging research area due to continuous modernization of various systems, for instance, Edge Computing. In this article, we present a novel malicious…
6G Communications: A Vision on the Potential Applications
Sabuzima Nayak, Ripon Patgiri
6G communication technology is a revolutionary technology that will revolutionize many technologies and applications. Furthermore, it will be truly AI-driven and will carry on inte…
6G Communication Technology: A Vision on Intelligent Healthcare
Sabuzima Nayak, Ripon Patgiri
6G is a promising communication technology that will dominate the entire health market from 2030 onward. It will dominate not only health sector but also diverse sectors. It is exp…
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…
6G Communication: Envisioning the Key Issues and Challenges
Sabuzima Nayak, Ripon Patgiri
In 2030, we are going to evidence the 6G mobile communication technology, which will enable the Internet of Everything. Yet 5G has to be experienced by people worldwide and B5G has…
Empirical Study on Airline Delay Analysis and Prediction
Ripon Patgiri, Sajid Hussain, Aditya Nongmeikapam
The Big Data analytics are a logical analysis of very large scale datasets. The data analysis enhances an organization and improve the decision making process. In this article, we…
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…
Machine Learning: A Dark Side of Cancer Computing
Ripon Patgiri, Sabuzima Nayak, Tanya Akutota +1
Cancer analysis and prediction is the utmost important research field for well-being of humankind. The Cancer data are analyzed and predicted using machine learning algorithms. Mos…
scaleBF: A High Scalable Membership Filter using 3D Bloom Filter
Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain
Bloom Filter is extensively deployed data structure in various applications and research domain since its inception. Bloom Filter is able to reduce the space consumption in an orde…
Role of Bloom Filter in Big Data Research: A Survey
Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain
Big Data is the most popular emerging trends that becomes a blessing for human kinds and it is the necessity of day-to-day life. For example, Facebook. Every person involves with p…
Preventing DDoS using Bloom Filter: A Survey
Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain
Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a ser…
A Taxonomy on Big Data: Survey
Ripon Patgiri
The Big Data is the most popular paradigm nowadays and it has almost no untouched area. For instance, science, engineering, economics, business, social science, and government. The…
MapReduce Scheduler: A 360-degree view
Rajdeep Das, Rohit Pratap Singh, Ripon Patgiri
Undoubtedly, the MapReduce is the most powerful programming paradigm in distributed computing. The enhancement of the MapReduce is essential and it can lead the computing faster. T…