Bikash Agrawal

Bikash Agrawal
University of Stavanger (UiS) · Department of Electrical engineering and Computer science

Doctor of Philosophy

About

12
Publications
10,334
Reads
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61
Citations
Additional affiliations
September 2015 - March 2016
Purdue University
Position
  • Researcher
October 2013 - present
University of Stavanger (UiS)
Position
  • PhD Student

Publications

Publications (12)
Conference Paper
Full-text available
This paper proposes a novel and scalable model for automatic anomaly detection on a large system such as a cloud. Anomaly detection issues early warning of unusual behavior in dynamic environments by learning system characteristic from normal operational data. Anomaly detection in large systems is difficult to detect due heterogeneity, dynamicity,...
Conference Paper
Full-text available
Sensitive information that is stored in Hadoop clusters can potentially be retrieved without permission or access granted. In addition, the ability to recover deleted data from Hadoop clusters represents a major security threat. Hadoop clusters are used to manage large amounts of data both within and outside of organizations. As a result, it has be...
Conference Paper
Full-text available
In this paper, we propose a novel approach to analyze and predict failures in Hadoop cluster. We enumerate several key challenges that hinder failure prediction in such systems: heterogeneity of the system, hidden complexity, time limitation and scalability. At first, clustering approach is applied to group similar error sequences, which makes trai...
Conference Paper
Data streams from various Internet-Of-Things (IOT) enabled sensors in smart homes provide an opportunity to develop predictive models to offer actionable insights in form of preventive care to its residence. This becomes particularly relevant for Aging-In-Place (AIP) solutions for the care of the elderly. Over the last decade, diverse stakeholders...
Article
Full-text available
Cloud computing has become increasingly popular, which has led many individuals and organizations towards cloud storage systems. This move is motivated by benefits such as shared storage, computation, and transparent service among a massive number of users. However, cloud-computing systems require the maintenance of complex and large-scale systems...
Conference Paper
The data collected from millions of public cameras needs to be retrieved, stored, and analyzed. A system is required which needs to allocate significant amounts of resources to analyze large-scale visual data. Cloud computing provides shared storage, computation, and various services to handle such a tremendous amount of data collected from distrib...
Thesis
Full-text available
In the current “information explosion era”, data is increasing dramatically every year. Tackling the challenges posed by collecting large-scale data is trending to a superabundance of data management systems characterized by horizontal scalability. Data has become a critical commodity in organizations and data ana- lysts are struggling to make opti...
Presentation
Full-text available
In recent years, the amount of time series data generated in different domains have grown consistently. Analyzing large time-series datasets coming from sensor networks, power grids, stock exchanges, social networks and cloud monitoring logs at a massive scale is one of the biggest challenges that data scientists are facing. Big data storage and pr...

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Projects

Project (1)
Archived project
ERAC stands for Efficient and Robust Architecture for the Big Data Cloud .This research project has the key objectives of processing and exploiting huge volumes of data. The project is led by Simula, and supported by participation from the University of Stavanger and the University of Oslo. Oracle is the other key partner in this project. ERAC is a research project supported by the VERDIKT programme. Two Ph.D fellows linked to the CIPSI centre at the University of Stavanger are also associated with the ERAC project. Through close collaboration with Oracle, Simula, the University of Oslo and the University of Stavanger, the consortium aims to be a leader in a core area such as cloud computing, which will form the backbone of services and applications in the Internet of the future. Other selected core areas for excellence are: (i) communications technology and infrastructure and ( ii ) security, privacy and vulnerability. The Consortium's main focus is on chosen problem areas such as rapid elasticity, scale, virtualization, simplicity and energy efficiency. Current cloud computing technology still experiences limitations in these areas.