adfa, p. 1, 2011. © Springer-Verlag Berlin Heidelberg 2011 Global Pricing in Large Scale Computational Markets Lilia Chourou 1 , Ahmed Elleuch 2 and Mohamed Jemni 1 1 LaTICE laboratory, Higher School of Sciences and Techniques of Tunis, University of Tunis, Tunis, Tunisia lilia.gherir@planet.tn, Mohamed.jemni@fst.rnu.tn 2 CRISTAL laboratory, National School of Computer Sciences, University of Manouba, Manouba, Tunisia Ahmed.Elleuch@ensi.rnu.tn Abstract. Scale up the number of computing resources is a challenging issue when building a global computational system. For this purpose, we present an approach that adopts the commodity market model as an economic incentive model and ensures the balance between supply and demand. We show how this model may be adapted and applied to a large scale computational infrastructure. To achieve a competitive equilibrium, prices are adjusted according to a tâton- nement like process. However, this process, like several other pricing algo- rithms proposed in the literature, does not fulfill the scalability requirement: all prices of all commodities are computed by only one auctioneer. In the present work, a fully distributed pricing algorithm is proposed based on an existing par- tially distributed version. While in this last version, the price of each commod- ity is computed by only one auctioneer, in our algorithm, a variable number of auctioneers is used. To each auctioneer is associated a limited number of con- sumers and suppliers with low communication delay. Our algorithm is then scalable with respect to the number of suppliers and consumers. To evaluate our algorithm, we have performed a simulation study. For different number of auc- tioneers per commodity, the experimental results show that our algorithm con- verges as well as the partially distributed version. Moreover, by splitting the search space among auctioneers, our algorithm accelerates the convergence. Keywords: pricing, competitive equilibrium, scalability, global computational system. 1 Introduction One major problem facing high-throughput applications is the need for large-scale computational resources. Global computing systems are a cost-effective alternative to parallel computers. They are able to provide a great number of idle resources donated by volunteers and accessible via the Internet. However, the number of available re- sources still needs to be expanded. For this purpose, we have to apply an economic incentive model that would allow increasing the number of suppliers and consumers by embedding a strategy for welfare. The economic model would also be used to re- solve the load balancing problem. In this paper, we have adopted the commodity mar-