Internet Marketplaces: The Law of Auctions and Exchanges Online
Internet Marketplaces: The Law of Auctions and Exchanges Online
The workload on parallel supercomputers: modeling the characteristics of rigid jobs
Journal of Parallel and Distributed Computing
Future Generation Computer Systems
GridEcon: A Market Place for Computing Resources
GECON '08 Proceedings of the 5th international workshop on Grid Economics and Business Models
Brief announcement: modelling MapReduce for optimal execution in the cloud
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
See spot run: using spot instances for mapreduce workflows
HotCloud'10 Proceedings of the 2nd USENIX conference on Hot topics in cloud computing
Managing Peak Loads by Leasing Cloud Infrastructure Services from a Spot Market
HPCC '10 Proceedings of the 2010 IEEE 12th International Conference on High Performance Computing and Communications
Decision Model for Cloud Computing under SLA Constraints
MASCOTS '10 Proceedings of the 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
RC2-a living lab for cloud computing
LISA'10 Proceedings of the 24th international conference on Large installation system administration
Combining Futures and Spot Markets: A Hybrid Market Approach to Economic Grid Resource Management
Journal of Grid Computing
Dynamic resource allocation for spot markets in clouds
Hot-ICE'11 Proceedings of the 11th USENIX conference on Hot topics in management of internet, cloud, and enterprise networks and services
Performance and cost assessment of cloud services
ICSOC'10 Proceedings of the 2010 international conference on Service-oriented computing
Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing
IEEE Transactions on Parallel and Distributed Systems
Tradeoffs Between Profit and Customer Satisfaction for Service Provisioning in the Cloud
Proceedings of the 20th international symposium on High performance distributed computing
Debunking Real-Time Pricing in Cloud Computing
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Resource Provisioning Policies to Increase IaaS Provider's Profit in a Federated Cloud Environment
HPCC '11 Proceedings of the 2011 IEEE International Conference on High Performance Computing and Communications
Achieving Performance and Availability Guarantees with Spot Instances
HPCC '11 Proceedings of the 2011 IEEE International Conference on High Performance Computing and Communications
Provisioning spot market cloud resources to create cost-effective virtual clusters
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
A Measurement Study of Server Utilization in Public Clouds
DASC '11 Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing
Deconstructing Amazon EC2 Spot Instance Pricing
CLOUDCOM '11 Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science
Workload analysis of a cluster in a grid environment
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Optimal Resource Rental Planning for Elastic Applications in Cloud Market
IPDPS '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium
Monetary Cost-Aware Checkpointing and Migration on Amazon Cloud Spot Instances
IEEE Transactions on Services Computing
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Cloud providers possessing large quantities of spare capacity must either incentivize clients to purchase it or suffer losses. Amazon is the first cloud provider to address this challenge, by allowing clients to bid on spare capacity and by granting resources to bidders while their bids exceed a periodically changing spot price. Amazon publicizes the spot price but does not disclose how it is determined. By analyzing the spot price histories of Amazon’s EC2 cloud, we reverse engineer how prices are set and construct a model that generates prices consistent with existing price traces. Our findings suggest that usually prices are not market-driven, as sometimes previously assumed. Rather, they are likely to be generated most of the time at random from within a tight price range via a dynamic hidden reserve price mechanism. Our model could help clients make informed bids, cloud providers design profitable systems, and researchers design pricing algorithms.