A Cloud Resource Allocation Scheme Based on Microeconomics and Wind Driven Optimization

As a new model of distributed computing, all kinds of distributed resources are virtualized to establish a shared resource pool through cloud computing. The target of cloud computing is to provide convenient and configurable resource for users with pay-per-usage charging model. Therefore, the reasonable and efficient mechanism for resource allocating is becoming a hot spot in research. According to the features of cloud resource allocation, methods of auction model, neural network and intelligent optimization are comprehensively applied in this paper for proposing a double multi-attribute auction based cloud resource allocation mechanism. In the mechanism, non-price attributes like quality of experience, level of delivery, level of payment and level of spiteful quote are described for better satisfying the requirements of users, and these attributes are transferred to an index of quality through BP neural network. Based on the history information of auction, support vector machine algorithm is utilized to predict the price in advance. In the end, using satisfaction extracted from index of quality and price as optimization goal, wind driven optimization algorithm is adopted to get the optimized allocation scheme. Simulation results have shown that the mechanism is feasible and effective.