Predicting Machine Availabilities in Desktop Pools

2010 IEEE 3rd International Conference on Cloud Computing

Andrzejak

2010

211

156

Abstract-Recently introduced spot instances in the AmazonElastic Compute Cloud (EC2) offer lower resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability trade-offs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how one such a mechanism, namely checkpointing, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive checkpointing schemes in terms of monetary costs and improvement of job completion times. Trace-based simulations show that our approach can reduce significantly both price and the task completion times.

Section: Related Workmentioning

confidence: 99%

Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud

2010 IEEE 3rd International Conference on Cloud Computing

Andrzejak

2010

211

156

“…A plethora of models and algorithm exist for analyzing, predicting, and resolving failures [6], [21], [15], [12], [20], [2], [1]. At best, these models and algorithms are evaluated using failure traces of a single or limited number of systems.…”

Section: Introductionmentioning

confidence: 99%

The Failure Trace Archive: Enabling Comparative Analysis of Failures in Diverse Distributed Systems

2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing

Javadi

Iosup

et al. 2010

140

111

. (2010). The failure trace archive : enabling comparative analysis of failures in diverse distributed systems. In Proceedings of the 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID'10, Melbourne, Australia, May 17-20, 2010) (pp. 398-407). Institute of Electrical and Electronics Engineers (IEEE). DOI: 10.1109/CCGRID.2010.71 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

“…The first one is finding the relationship between past and future failures or availability for proactive checkpointing. Much work exists on finding correlations and dependence between failure events [23], [24], [25], [26]. Another challenge is using an efficient checkpointing method for minimizing the expected execution time in the presence of failures.…”

Section: Related Workmentioning

confidence: 99%

Monetary Cost-Aware Checkpointing and Migration on Amazon Cloud Spot Instances

Andrzejak

IEEE Trans. Serv. Comput.

2012

140

International audienceRecently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer low resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability tradeoffs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how mechanisms, namely, checkpointing and migration, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive checkpointing schemes in terms of monetary costs and improvement of job completion times. We evaluate schemes that apply predictive methods for spot prices. Furthermore, we also study how work migration can improve task completion in the midst of failures while maintaining low monetary costs. Trace-based simulations show that our schemes can reduce significantly both monetary costs and task completion times of computation on spot instance