Khadija Bibi

Work place: GC Women University Sialkot/ Department of Computer Science & Information Technology, Pakistan

E-mail: info.tec15018@gcwus.edu.pk

Website:

Research Interests: Computer systems and computational processes, Autonomic Computing, Computer Architecture and Organization, Data Structures and Algorithms, Programming Language Theory

Biography

Khadija Aashiq born in Sialkot in 1997. She did her matriculation level in 2013 from Government Girls Higher Secondary School, Ugoki Sialkot in Science Subjects and her intermediate level (I.C.S) in 2015 from Government Girls Higher Secondary College Ugoki Sialkot. Now she is doing her BS (Hons) in Information Technology (IT) from GC WOMEN UNIVERSITY, Sialkot. She attended ethical hacking workshop at University of Gujarat and also certified as Microsoft Office specialist. Currently she has been working on research as final year project in Cloud Computing topic. Her main areas of research interest are Cloud Computing, primary dangerous computer viruses, Data Base and Programming Languages.

Author Articles
Prediction and Monitoring Agents using Weblogs for improved Disaster Recovery in Cloud

By Rushba Javed Sidra Anwar Khadija Bibi M. Usman Ashraf Samia Siddique

DOI: https://doi.org/10.5815/ijitcs.2019.04.02, Pub. Date: 8 Apr. 2019

Disaster recovery is a continuous dilemma in cloud platform. Though sudden scaling up and scaling down of user’s resource requests is available, the problem of servers down still persists getting users locked at vendor’s end. This requires such a monitoring agent which will reduce the chances of disaster occurrence and server downtime. To come up with an efficient approach, previous researchers’ techniques are analyzed and compared regarding prediction and monitoring of outages in cloud computing. A dual functionality Prediction and Monitoring Agent is proposed to intelligently monitor users’ resources requests and to predict coming surges in web traffic using Linear Regression algorithm. This solution will help to predict the user’s future requests’ behavior, to monitor current progress of resources’ usage, server virtualization and to improve overall disaster recovery process in Cloud Computing.

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