A genetic model for pricing in cloud computing markets

Cloud Computing markets arise as an efficient way to allocate resources for the execution of tasks and services within a set of geographically dispersed providers from different organisations. Client applications and service providers meet in a market and negotiate for the sales of services by means of the signature of a Service Level Agreement. Depending on the status of the demand, the provider is able to offer higher or lower prices for maximising its profit. It is difficult to establish a profitable pricing function in competitive markets, because there are several factors that can influence in the prices. This paper deals with the problem of offering competitive prices in the negotiation of services in Cloud Computing markets. A Genetic Algorithms approach is proposed, in which a naive pricing function evolves to a pricing function that offers suitable prices in function of the system status. Its results are compared with other pricing strategies, demonstrating its validity.

[1]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[2]  M. Lloret,et al.  Influence of reputation in revenue of grid service providers , 2008 .

[3]  R. Buyya,et al.  Market-Oriented Grid and Utility Computing , 2009 .

[4]  Rajarshi Das,et al.  Agent-Human Interactions in the Continuous Double Auction , 2001, IJCAI.

[5]  Shu-Heng Chen.  Evolutionary Computation in Economics and Finance , 2002 .

[6]  Stephan M. Winkler,et al.  Genetic Algorithms and Genetic Programming , 2010 .

[7]  Dirk Neumann,et al.  Semi-Automated Provisioning and Usage of Configurable Web Services , 2008, ECIS.

[8]  Magda Bahaa Eldin Fayek,et al.  GAMA (genetic algorithm driven multi-agents)for e-commerce integrative negotiation , 2009, GECCO '09.

[9]  W. Marsden.  I and J , 2012 .

[10]  Dave Cliff,et al.  Evolution of market mechanism through a continuous space of auction-types , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[11]  Rajkumar Buyya,et al.  Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities , 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

[12]  Michael A. Rappa,et al.  The utility business model and the future of computing services , 2004, IBM Syst. J..

[13]  F. Black,et al.  The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.

[14]  Leandro Navarro-Moldes,et al.  Towards the development of a decentralized market information system: Requirements and architecture , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[15]  Shu-Heng Chen,et al.  Genetic Algorithms and Genetic Programming in Computational Finance , 2002 .

[16]  Joaguin R. Trigueros,et al.  An Adaptive Evolutionary Approach to Option Pricing Via Genetic Programming , 1998 .

[17]  Mario Macías,et al.  Using resource-level information into nonadditive negotiation models for cloud Market environments , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.