Generalized Nash Equilibria for the Service Provisioning Problem in Cloud Systems

Recently, the evolution and widespread adoption of virtualization, SOA, autonomic, and utility computing have converged letting a new paradigm to emerge: Cloud computing. Currently the Cloud offer is becoming wider and wider, since all the major IT Companies and Service providers have started providing solutions. As Cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies becomes increasingly challenging. In this paper we take the perspective of SaaS providers which host their applications at an IaaS. Each SaaS needs to comply with QoS requirements, specified in SLA contracts with the end-users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while competing and bidding for the use of infrastructural resources. In this paper we model the service provisioning problem as a generalized Nash game and we show the existence of equilibria for such game. Moreover, we propose two solution methods based on the best-reply dynamics and we prove their convergence in a finite number of iterations to a generalized Nash equilibrium. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2.