Paper Info
Title
SpotOn: a batch computing service for the spot market
Abstract
Cloud spot markets enable users to bid for compute resources, such that the cloud platform may revoke them if the market price rises too high. Due to their increased risk, revocable resources in the spot market are often significantly cheaper (by as much as 10×) than the equivalent non-revocable on-demand resources. One way to mitigate spot market risk is to use various fault-tolerance mechanisms, such as checkpointing or replication, to limit the work lost on revocation. However, the additional performance overhead and cost for a particular fault-tolerance mechanism is a complex function of both an application's resource usage and the magnitude and volatility of spot market prices. We present the design of a batch computing service for the spot market, called SpotOn, that automatically selects a spot market and fault-tolerance mechanism to mitigate the impact of spot revocations without requiring application modification. SpotOn's goal is to execute jobs with the performance of on-demand resources, but at a cost near that of the spot market. We implement and evaluate SpotOn in simulation and using a prototype on Amazon's EC2 that packages jobs in Linux Containers. Our simulation results using a job trace from a Google cluster indicate that SpotOn lowers costs by 91.9% compared to using on-demand resources with little impact on performance.
Year
DOI
Venue
2015
10.1145/2806777.2806851
IEEE International System-on-Chip (SoC) Conference
Keywords
Field
DocType
Spot Market,Fault-tolerance,Batch job
Computer science,Market price,Real-time computing,Revocation,Fault tolerance,Batch processing,Volatility (finance),Database,Operating system,Cloud computing,Spot market
Conference
Citations 
PageRank 
References 
35
1.05
17
Authors
5
Name
Order
Citations
PageRank
Supreeth Subramanya1452.36
Tian Guo2965.34
Prateek Sharma320114.12
David E. Irwin489998.12
Prashant J. Shenoy56386521.30