https://www-sop.inria.fr/members/Eitan.Altman/PAPERS/srvUpdate.pdf

A survey on networking games in telecommunications

In recent years, the evolution and the widespread adoption of virtualization, service-oriented architectures, autonomic, and utility computing have converged letting a new paradigm to emerge: cloud computing. Clouds allow the on-demand delivering of software, hardware, and data as services. Currently, the cloud offer is becoming wider day by day because all the major IT companies and service providers, like Microsoft, Google, Amazon, HP, IBM, and VMWare, have started providing solutions involving this new technological paradigm. 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 Software as a Service (SaaS) providers that host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality-of-service requirements, specified in service-level agreement (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 minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized 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. In particular, we develop an efficient distributed algorithm for the runtime allocation of IaaS resources among competing SaaS providers. We demonstrate the effectiveness of our approach by simulation and performing tests on a real prototype environment deployed on Amazon EC2. Results show that, compared to other state-of-the-art solutions, our model can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy by 50-70 percent.

/pdf/generalized-nash-equilibria-for-the-service-provisioning-2knz14c85z.pdf

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Cloud computing is an emerging paradigm which allows the on-demand delivering of software, hardware, and data as services. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies become increasingly challenging. Game theoretic approaches have shown to gain a thorough analytical understanding of the service provisioning problem.In this paper we take the perspective of Software as a Service (SaaS) providers which host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality of service requirements, specified in Service Level Agreement (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 minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper we model the service provisioning problem as a Generalized Nash game, and we propose an efficient algorithm for the run time management and allocation of IaaS resources to competing SaaSs.

/pdf/a-game-theoretic-formulation-of-the-service-provisioning-2f10h62ifv.pdf

A game theoretic formulation of the service provisioning problem in cloud systems

Games with coupled propagated constraints in optical networks with multi-link topologies

We consider the problem of selfish routing in a congested network shared by several users, where each user wishes to minimize the cost of its own flow. Users are atomic, in the sense that each has a nonnegligible amount of flow demand, and flows may be split over different routes. The total cost for each user is the sum of its link costs, which, in turn, may depend on the user's own flow as well as the total flow on that link. Our main interest here is network topologies that ensure uniqueness of the Nash equilibrium for any set of users and link cost functions that satisfy some mild convexity conditions. We characterize the class of two-terminal network topologies for which this uniqueness property holds, and show that it coincides with the class of nearly parallel networks that was recently shown by Milchtaich [Milchtaich, I. 2005. Topological conditions for uniqueness of equilibrium in networks. Math. Oper. Res.30 225--244] to ensure uniqueness in nonatomic (or Wardrop) routing games. We further show that uniqueness of the link flows holds under somewhat weaker convexity conditions, which apply to the mixed Nash-Wardrop equilibrium problem. We finally propose a generalized continuum-game formulation of the routing problem that allows for a unified treatment of atomic and nonatomic users.

Topological Uniqueness of the Nash Equilibrium for Selfish Routing with Atomic Users

We study noncooperative routing in which each user is faced with a multicriterion optimization problem, formulated as the minimization of one criterion subject to constraints on others. We address the questions of existence and uniqueness of equilibrium. We show that equilibria indeed exist but uniqueness may be destroyed due to the multicriteria nature of the problem. We obtain uniqueness in some weaker sense under appropriate conditions: we show that the link utilizations are uniquely determined at equilibrium. We further study the normalized constrained equilibrium and apply it to pricing.

/pdf/constrained-traffic-equilibrium-in-routing-cwrusbpbvv.pdf

Constrained traffic equilibrium in routing

Considers the problem of the perturbation of a class of linear quadratic systems where the change from one structure (for the dynamics and costs) to another is governed by a finite-state Markov process. The problem above leads to the analysis of some perturbed linearly coupled sets of Riccati equations. We show that the matrix obtained as the solution of the equations, which determines the optimal value and control, has a Taylor expansion in the perturbation parameter. We compute explicitly the terms of this expansion.

R. El Azouzi

Papers

Constrained traffic equilibrium in routing

Perturbation of multivariable linear quadratic systems with jump parameters