Automated Tracking, Reliable and Monitoring of Cloud Resources
 |
International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2018 by IJCTT Journal | ||
| Volume-61 Number-1 |
||
| Year of Publication : 2018 | ||
| Authors : Kailash Basawaraj, Assoc.Prop. Chandrakant Biradar | ||
| DOI : 10.14445/22312803/IJCTT-V61P107 |
MLA Style: Kailash Basawaraj, Assoc.Prop. Chandrakant Biradar "Automated Tracking, Reliable and Monitoring of Cloud Resources" International Journal of Computer Trends and Technology 61.1 (2018): 35-38.
APA Style:Kailash Basawaraj, Assoc.Prop. Chandrakant Biradar (2018). Automated Tracking, Reliable and Monitoring of Cloud Resources. International Journal of Computer Trends and Technology, 61(1), 35-38.
Abstract
To discuss about an efficient and effective framework to automatically track ,monitor, and orchestrate resource usage in an infrastructure as a service(IaaS) system.This section provides the finding anomalies and user behaviors through given data.After finding anomalies user and send to detection phase with send to cloud server.We use novel tracking method to continuously track important system usage metrices with low overhead,and develop a Principal Component Analysis(PCA) based approach to continuously monitor and automatically find anomalies based on the approximated tracking results.We show how to dynamically set the tracking threshold under dynamic workloads.Honeypot-based deception mechanism has been considered as one of the methods to ensure security for modern networks in the Internet of Things(IoT).
Reference
[1] D.Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, and D. Zagorodnov, “The eucalyptus open-source cloud-computing system,” in CCGRID, pages 120-124,2009.
[2] W.Dawoud, I. Takouna, and C. Meinel, “Infrastructure as a service security: Challenges and solutions,” in INFOS, pages 49-55 2010.
[3] D.J.Dean, H. Nguyen, and X. Gu, “Ubl: Unsupervised behavior learning for predicting performance anomalies in virtualized cloud systems,” in ICAC, pages 23-29 2012.
[4] M.Amin and A. M. Giacomoni, “Smart grid- safe, secure, self-healing: Challenges and opportunities in power system security, resiliency, and privacy,” IEEE Power Energy Mag., vol. 10, no. 1, pages 33–40, Jan./Feb. 2012.
[5] Zhang and B. Qu, “Security architecture of the Internet of Things oriented to perceptual layer,” Int. J. Compute. Consume. Control, vol. 2, no. 2, pages. 37–45, 2013.
Keywords
Principal Component Analysis, Find abnormal events, Task Scheduling