A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems
IEEE Transactions on Computers
Adaptive load sharing in heterogeneous distributed systems
Journal of Parallel and Distributed Computing
Optimal decentralized flow control of Markovian queueing networks with multiple controllers
Performance Evaluation
On the existence of equilibria in noncooperative optimal flow control
Journal of the ACM (JACM)
Queueing networks and Markov chains: modeling and performance evaluation with computer science applications
Nash equilibria, variational inequalities, and dynamical systems
Journal of Optimization Theory and Applications
Sharc: Managing CPU and Network Bandwidth in Shared Clusters
IEEE Transactions on Parallel and Distributed Systems
Resource Allocation for Autonomic Data Centers using Analytic Performance Models
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Noncooperative load balancing in distributed systems
Journal of Parallel and Distributed Computing
Power and Performance Management of Virtualized Computing Environments Via Lookahead Control
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
Game based capacity allocation for utility computing environments
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
Load balancing in processor sharing systems
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
Cutting the electric bill for internet-scale systems
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
A survey on networking games in telecommunications
Computers and Operations Research
Joint admission control and resource allocation in virtualized servers
Journal of Parallel and Distributed Computing
A new game theoretical resource allocation algorithm for cloud computing
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments
IEEE Transactions on Services Computing
The Aumann-Shapley price mechanism for allocating congestion costs
Operations Research Letters
Role assignment in institutional clouds for rule-based enterprise management
RuleML'11 Proceedings of the 5th international conference on Rule-based modeling and computing on the semantic web
Coordination, conventions and the self-organisation of sustainable institutions
PRIMA'11 Proceedings of the 14th international conference on Agents in Principle, Agents in Practice
Self-managing SLA compliance in cloud architectures: a market-based approach
Proceedings of the 3rd international ACM SIGSOFT symposium on Architecting Critical Systems
Economic model based cloud service composition
ICSOC'11 Proceedings of the 2011 international conference on Service-Oriented Computing
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special Section: Extended Version of SASO 2011 Best Paper
Computational Aspects of Uncertainty Profiles and Angel-Daemon Games
Theory of Computing Systems
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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.