An efficient cloud resource exchange model based on the double auction and evolutionary game theory

One of the most well-known ways for cloud service providers (CSPs) to satisfy customers and reduce SLA violations is to offer resources through an auction market. In previous research based on classical games, the CSP has been considered as a player. A drawback of this type of modeling is that it is not scalable as the number of CSPs increases. In this paper, we use the combination of barter and evolutionary game theory to model the exchange of VM instances among CSPs. First, each CSP estimates the free and used resources. Then, according to the estimated valuation, the CSP announces its bid as a strategy to the auctioneer. We use evolutionary game theory to update the strategy of CSPs and increase their winning probability. The proposed method does not require any monetary exchange or registration of separate contracts between CSPs. In case of an SLA violation, a CSP can reclaim its rented resources from the other party. Moreover, since the violation of the agreement is costly for the violating party, the motivation for cooperation between CSPs increases. The simulation results show that the proposed model can lead to a 5% improvement in social welfare compared to the state-of-the-art barter double auction methods. Moreover, in addition to increasing the payoff of CSPs, it reduces the number of contracts by 3%.

Automated summary

The paper proposes a method to model the exchange of VM instances among CSPs using a combination of barter and evolutionary game theory. The proposed model does not require monetary exchange or separate contracts, and it leads to a 5% improvement in social welfare and a 3% reduction in the number of contracts.