SipaaS: Spot instance pricing as a Service framework and its implementation in OpenStack

Designing dynamic pricing mechanisms that efficiently price resources in line with a provider's profit maximization goal is a key challenge in cloud computing environments. Despite the large volume of research published on this topic, there is no publicly available software system implementing dynamic pricing for Infrastructure as a Service cloud spot markets. This paper presents the implementation of a framework called Spot instance pricing as a Service (SipaaS) that supports an auction mechanism to price and allocate virtual machine instances. SipaaS is an open‐source project offering a set of web services to price and sell virtual machine instances in a spot market resembling the Amazon EC2 spot instances. Cloud providers, who aim at utilizing SipaaS, should install add‐ons in their existing platform to make use of the framework. As an instance, we provide an extension to the Horizon – the OpenStack dashboard project – to employ SipaaS web services and to add a spot market environment to OpenStack. To validate and evaluate the system, we conducted an experimental study with a group of 10 users utilizing the provided spot market in a real environment. Results show that the system performs reliably in a practical test environment. Copyright © 2015 John Wiley & Sons, Ltd.

[1]  Satoshi Fujita,et al.  Truthful Allocation of Virtual Machine Instances with the Notion of Combinatorial Auction , 2014, 2014 Second International Symposium on Computing and Networking.

[2]  Verena Kantere,et al.  Optimal Service Pricing for a Cloud Cache , 2011, IEEE Transactions on Knowledge and Data Engineering.

[3]  Muli Ben-Yehuda,et al.  Deconstructing Amazon EC2 Spot Instance Pricing , 2011, CloudCom.

[4]  Baochun Li,et al.  Dynamic Cloud Pricing for Revenue Maximization , 2013, IEEE Transactions on Cloud Computing.

[5]  Mark Klein,et al.  Auctions and bidding: A guide for computer scientists , 2011, CSUR.

[6]  Mariella Di Giacomo MySQL: Lessons Learned on a Digital Library , 2005, IEEE Softw..

[7]  Roger B. Myerson,et al.  Optimal Auction Design , 1981, Math. Oper. Res..

[8]  Anna R. Karlin,et al.  Competitive auctions , 2006, Games Econ. Behav..

[9]  Artur Andrzejak,et al.  Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[10]  Ariel Ortiz Ramirez Three-Tier Architecture , 2000 .

[11]  Baochun Li,et al.  Revenue maximization with dynamic auctions in IaaS cloud markets , 2013, 2013 IEEE/ACM 21st International Symposium on Quality of Service (IWQoS).

[12]  Tram Truong-Huu,et al.  A Novel Model for Competition and Cooperation among Cloud Providers , 2014, IEEE Transactions on Cloud Computing.

[13]  Kwang Mong Sim,et al.  A Price- and-Time-Slot-Negotiation Mechanism for Cloud Service Reservations , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Zongpeng Li,et al.  An Online Auction Framework for Dynamic Resource Provisioning in Cloud Computing , 2016, IEEE/ACM Transactions on Networking.

[15]  Muriati Mukhtar,et al.  A combinatorial double auction resource allocation model in cloud computing , 2016, Inf. Sci..

[16]  Rajkumar Buyya,et al.  Multi-Cloud Provisioning and Load Distribution for Three-Tier Applications , 2014, TAAS.

[17]  Yang Song,et al.  Optimal bidding in spot instance market , 2012, 2012 Proceedings IEEE INFOCOM.

[18]  Carrie Grimes,et al.  Using a market economy to provision compute resources across planet-wide clusters , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[19]  Daniel Grosu,et al.  Combinatorial Auction-Based Allocation of Virtual Machine Instances in Clouds , 2010, CloudCom.

[20]  Baochun Li,et al.  Towards Optimal Capacity Segmentation with Hybrid Cloud Pricing , 2012, 2012 IEEE 32nd International Conference on Distributed Computing Systems.

[21]  Athanasios V. Vasilakos,et al.  A Framework for Truthful Online Auctions in Cloud Computing with Heterogeneous User Demands , 2016, IEEE Transactions on Computers.

[22]  Bu-Sung Lee,et al.  Economic analysis of resource market in cloud computing environment , 2009, 2009 IEEE Asia-Pacific Services Computing Conference (APSCC).

[23]  Rajkumar Buyya,et al.  Reliable Provisioning of Spot Instances for Compute-intensive Applications , 2011, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications.

[24]  Rod Johnson,et al.  Professional Java Development with the Spring Framework , 2005 .

[25]  Bo Li,et al.  Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers , 2014, IEEE Transactions on Computers.

[26]  Rajkumar Buyya,et al.  An Auction Mechanism for Cloud Spot Markets , 2016, TAAS.

[27]  Kai Song,et al.  Exploring the profit-reliability trade-off in Amazon's spot instance market: A better pricing mechanism , 2013, 2013 IEEE/ACM 21st International Symposium on Quality of Service (IWQoS).

[28]  Adel Nadjaran Toosi,et al.  On the economics of infrastructure as a service cloud providers: pricing, markets, and profit maximization , 2014 .

[29]  Martin Fowler,et al.  Patterns of Enterprise Application Architecture , 2002 .

[30]  Rajkumar Buyya,et al.  Fault-tolerant Workflow Scheduling using Spot Instances on Clouds , 2014, ICCS.

[31]  Douglas Crockford,et al.  The application/json Media Type for JavaScript Object Notation (JSON) , 2006, RFC.

[32]  Xue Liu,et al.  Present or Future: Optimal Pricing for Spot Instances , 2013, 2013 IEEE 33rd International Conference on Distributed Computing Systems.

[33]  Guihai Chen,et al.  STAR: Strategy-Proof Double Auctions for Multi-Cloud, Multi-Tenant Bandwidth Reservation , 2015, IEEE Transactions on Computers.

[34]  Nancy Samaan,et al.  A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers , 2014, IEEE Transactions on Parallel and Distributed Systems.

[35]  Dirk Neumann,et al.  Management of Cloud Infastructures: Policy-Based Revenue Optimization , 2009, ICIS.

[36]  Cesare Pautasso,et al.  Restful web services vs. "big"' web services: making the right architectural decision , 2008, WWW.

[37]  Bo An,et al.  Automated negotiation with decommitment for dynamic resource allocation in cloud computing , 2010, AAMAS.

[38]  Rajkumar Buyya,et al.  Characterizing spot price dynamics in public cloud environments , 2013, Future Gener. Comput. Syst..

[39]  Mario Macías,et al.  Rule-based SLA management for revenue maximisation in Cloud Computing Markets , 2010, 2010 International Conference on Network and Service Management.

[40]  Apostolos Papageorgiou,et al.  Maximizing Cloud Provider Profit from Equilibrium Price Auctions , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[41]  Yong Meng Teo,et al.  Dynamic Resource Pricing on Federated Clouds , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[42]  Quanyan Zhu,et al.  Dynamic Resource Allocation for Spot Markets in Cloud Computing Environments , 2011, 2011 Fourth IEEE International Conference on Utility and Cloud Computing.

[43]  Asser N. Tantawi,et al.  See Spot Run: Using Spot Instances for MapReduce Workflows , 2010, HotCloud.

[44]  Baochun Li,et al.  A study of pricing for cloud resources , 2013, PERV.