By Topic

Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private Clouds

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Feller, E. ; INRIA Centre Rennes, Campus Univ. de Beaulieu, Rennes, France ; Rilling, L. ; Morin, C.

With the advent of cloud computing and the need to satisfy growing customers resource demands, cloud providers now operate increasing amounts of large data centers. In order to ease the creation of private clouds, several open-source Infrastructure-as-a-Service (IaaS) cloud management frameworks (e.g. Open Nebula, Nimbus, Eucalyptus, Open Stack) have been proposed. However, all these systems are either highly centralized or have limited fault tolerance support. Consequently, they all share common drawbacks: scalability is limited by a single master node and Single Point of Failure (SPOF). In this paper, we present the design, implementation and evaluation of a novel scalable and autonomic (i.e. self-organizing and healing) virtual machine (VM) management framework called Snooze. For scalability the system utilizes a self-organizing hierarchical architecture and performs distributed VM management. Moreover, fault tolerance is provided at all levels of the hierarchy, thus allowing the system to self-heal in case of failures. Our evaluation conducted on 144 physical machines of the Grid'5000 experimental test bed shows that the fault tolerance features of the framework do not impact application performance. Moreover, negligible cost is involved in performing distributed VM management and the system remains highly scalable with increasing amounts of resources.

Published in:

Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on

Date of Conference:

13-16 May 2012