A new cost-effective mechanism for VM-to-user mapping in cloud data centers

Abstract

Attracting customers through reward programs is the primary key success for customer-oriented organizations. One of the most famous customer reward programs is applying price discount. In our negotiation-based cloud resource allocation problem, discount price is offered based on both status of a provider and behavior (or loyalty class) of a customer. That is, a resource customer who has appropriate buying behavior and negotiates for resource type instances with high necessity to sell is deserved to receive high price discount from provider. To do this, first, three customer’s loyalty classes are defined and customers are classified into theses classes in terms of their previous buying behavior using fuzzy system in name FCLCDS. Second, another fuzzy system in name FNTSVMTDS is designed to determine the value of necessity to sell resource type. The outputs of FCLCDS and FNTSVMTDS are called Loyalty Class (LC) and Necessity to Sell VM Type (NtSVMT), respectively. Finally, a fuzzy system in name FDCDS is proposed to determine the discount coefficient based on both LC and NtSVMT inputs. Furthermore, appropriate times for calculating/re-calculating the discount coefficients that are applied by a resource provider to relax its counter-offers are calculated. We perform extensive simulation experiments to compare our designed negotiator in name FDMDA with MDA and FNSSA. The results show that our designed FDMDA outperforms MDA and FNSSA.