A fair multi-attribute combinatorial double auction model for resource allocation in cloud computing

• Considers multi-attribute combinatorial double auction for winner determination.
• Imposes penalty on provider offering false QoS assurance and compensates the users.
• Reputation of provider is also being considered to prevent the cheating.
• Fairness to reduce the dissatisfaction of bidders is also included in the model.
• Evaluation by simulation and on auction properties shows the effectiveness of model.

Recently, Cloud computing has emerged as a market where computing related resources are treated as a utility and are priced. There is a big competition among the Cloud service providers and therefore, the providers offer the services strategically. Auction, a market based resource allocation strategy, has received the attention among the Cloud researchers recently. The auction principal of resource allocation is based on demand and supply. This work proposes a multi-attribute combinatorial double auction for the allocation of Cloud resources, which not only considers the price but other quality of service parameters also. Auctioneer extends some of the parameters to the offered bids from the bidders in order to provide fairness and robustness. In case of not meeting the assured quality, a penalty is imposed on the provider and customer is compensated. The reputation of the provider also diminishes in the forthcoming rounds. Performance study of the proposed model is done by simulation which reflects the usefulness of the method.