The Library

A modular failure-aware resource allocation architecture for cloud computing

Tools

Chester, Adam P., Leeke, Matthew, Al-Ghamdi, M., Jarvis, Stephen A., 1970- and Jhumka, Arshad (2011) A modular failure-aware resource allocation architecture for cloud computing. In: UK Performance Engineering Workshop (UKPEW'11), Bradford, United Kingdom, 7-8 July 2011

Preview

PDF
UKPEW11.pdf - Published Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (296Kb) | Preview

Official URL: http://www.inf.brad.ac.uk/ukpew11/index.php

Abstract

The prevalence of cloud computing environments and the ever increasing reliance of large organisations on computational resources has meant that service providers must operate at unprecedented scales and levels of efficiency. Dynamic resource allocation (DRA) policies have been shown to allow service providers to improve resource utilisation and operational efficiency in presence of unpredictable demands, hence maximising profitability. However, practical considerations, such as power and space, have led service providers to adopt rack based approaches to application servicing. This co-location of computation resources, and the associated common provision of utilities it encourages, has immediate implications for system dependability. Specifically, in the presence of rack crash failures which can lead to all the servers within a rack becoming unavailable, resource allocation policies need to be cognisant of failures. In this paper, we address this issue and make the following specific contributions: (i) we present a modular architecture for failure-aware resource allocation, where a performance- oriented DRA policy is composed with a failure-aware resource allocator, (ii) we propose a metric, called Capacity Loss, to capture the exposure of an application to a rack failure, (iii) we develop an algorithm for reducing the proposed metric across all applications in a system operating under a DRA policy, and (iv) we evaluate the effectiveness of the proposed architecture on a large-scale DRA policy in context of rack failures, ultimately concluding that our approach reduces the number of failed requests as compared to a single random allocation. The main benefit of our approach is that we have developed a failure-aware resource allocation framework that can work in tandem with any DRA policy.

Item Type:

Conference Item (Paper)

Subjects:

Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software

Divisions:

Faculty of Science > Computer Science

Library of Congress Subject Headings (LCSH):

Cloud computing, Resource allocation, Fault-tolerant computing

Official Date:

July 2011

Dates:

Date	Date Type
July 2011	Available

Status:

Peer Reviewed

Publication Status:

Published

Access rights to Published version:

Restricted or Subscription Access

Conference Paper Type:

Paper

Title of Event:

UK Performance Engineering Workshop (UKPEW'11)

Type of Event:

Workshop

Location of Event:

Bradford, United Kingdom

Date(s) of Event:

7-8 July 2011

References:

1. M. Al-Ghamdi, A. Chester, and S. Jarvis. Predictive and dynamic resource application for
enterprise applications. In Proceedings of the 10th IEEE International Conference on Scalable
Computing and Communications, pages 2776–2783, June 2010.
2. J. S. Chase, D. E. Irwin, L. E. Grit, J. D. Moore, and S. E. Sprenkle. Dynamic virtual
clusters in a grid site manager. In Proceedings of the 12th International Symposium on High
Performance Distributed Computing, pages 90–100, June 2003.
3. A. P. Chester, J. W. J. Xue, L. He, and S. A. Jarvis. A system for dynamic server allocation in
application server clusters. In Proceedings of the International Symposium on Parallel and
Distributed Processing with Applications, pages 130–139, December 2008.
4. L. He, W. J. Xue, and S. A. Jarvis. Partition-based profit optimisation for multi-class requests
in clusters of servers. In Proceedings of the International Conference on e-Business
Engineering, pages 131–138, October 2007.
5. J. Idziorek. Discrete event simulation model for analysis of horizontal scaling in the cloud
computing model. In Proceedings of the Winter Simulation Conference, pages 3004–3014,
December 2010.
6. P. Joshi, H. S. Gunawi, and K. Sen. Prefail: Programmable and efficient failure testing
framework. Ucb/eecs-2011-3, University of California at Berkeley, 2011.
7. X. Liu, J. Heo, and L.Sha. Modeling 3-tiered web applications. In Proc. International
Symposium on Modeling, Analysis and Simulation of Computer and Telecommunications
Systems, 2005.
8. D. A. Patterson. A simple way to estimate the cost of downtime. In Proceedings of the 16th
USENIX Systems Administration Conference, pages 185–188, November 2002.
9. K. Shvachko, H. Kuang, S. Radia, and R. Chansler. The hadoop distributed file system. In
Proceedings of the 26th IEEE Symposium on Mass Storage Systems and Technologies, pages
1–10, May 2010.
10. J. Slegers, I. Mitriani, and N. Thomas. Evaluating the optimal server allocation policy for
clusters with on/off sources. Journal of Performance Evaluation, 66(8):453–467, August
2009.
11. G. Tian and D. Meng. Failure rules based node resource provisioning policy for cloud computing.
In Proceedings of the International Symposium on Parallel and Distributed Processing
with Applications, pages 397–404, December 2010.
12. B. Urgaonkar and A. Chandra. Dynamic provisioning of multi-tier internet applications. In
Proceedings of the 2nd International Conference on Autonomic Computing, pages 217–228,
September 2005.
13. B. Urgaonkar, G. Pacifi, P. Shenoy, M. Spreitzer, and A. Tantawi. An analytical model for
multi-tier internet services and its applications. In Proceedings of the ACM SIGMETRICS
International Conference on Measurement and Modelling of Computer Systems, June 2005.
14. L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner. A break in the clouds:
towards a cloud definition. ACM SIGCOMM Computer Communication Review, 39(1):50–
55, January 2008.
15. K. V. Vishwanath and N. Nagappan. Characterizing cloud computing hardware reliability.
In Proceedings of the 1st ACM Symposium on Cloud Computing, pages 193–204, June 2010.
16. M. Wiboonrat. An empirical study on data center system failure diagnosis. In Proceedings
of the 3rd International Conference on Internet Monitoring and Protection, pages 103–108,
June 2008.
17. J. Xue, A. Chester, L. He, and S. Jarvis. Dynamic resource allocation in enterprise systems.
In Proceedings of the 14th International Conference on Parallel and Distributed Systems,
pages 203–212, December 2008.
18. Q. Zhang, L. Cherkasova, and E. Smirni. A regression-based analytical model for dynamic
resource provisioning of multi-tier applications. In Proceedings of the 4th International
Conference on Autonomic Computing, June 2007.