By Topic

Failure-Aware Construction and Reconfiguration of Distributed Virtual Machines for High Availability Computing

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

1 Author(s)
Song Fu ; Dept. of Comput. Sci., New Mexico Inst. of Min. & Technol., Socorro, NM

In large-scale clusters and computational grids, component failures become norms instead of exceptions. Failure occurrence as well as its impact on system performance and operation costs have become an increasingly important concern to system designers and administrators. In this paper, we study how to efficiently utilize system resources for high-availability clusters with the support of the virtual machine (VM) technology. We design a reconfigurable distributed virtual machine (RDVM) infrastructure for clusters computing. We propose failure-aware node selection strategies for the construction and reconfiguration of RDVMs. We leverage the proactive failure management techniques in calculating nodes' reliability status. We consider both the performance and reliability status of compute nodes in making selection decisions. We define a capacity-reliability metric to combine the effects of both factors in node selection, and propose best-fit algorithms to find the best qualified nodes on which to instantiate VMs to run parallel jobs. We have conducted experiments using failure traces from production clusters and the NAS parallel benchmark programs on a real cluster. The results show the enhancement of system productivity and dependability by using the proposed strategies. With the best-fit strategies, the job completion rate is increased by 17.6% compared with that achieved in the current LANL HPC cluster, and the task completion rate reaches 91.7%.

Published in:

Cluster Computing and the Grid, 2009. CCGRID '09. 9th IEEE/ACM International Symposium on

Date of Conference:

18-21 May 2009