A Novel Algorithm for Estimating Purchase Incentive of the Public Based on Mobile Cloud Computing

Abstract

Mobile cloud computing provides applications of cloud computing technology on mobile Internet. In the era of the 5G networks, mobile cloud computing offers the possibility of heavy computational in parallel through different mobile terminals. This also offers us to use mobile cloud computing to analyze fluctuations in user buying incentives over the course of a year. In various business scenarios, the purchase incentive of the public is often considered as being controlled by multiple factors and changes dramatically during holiday seasons. This paper proposed an evolutionary algorithm for monitoring purchase incentive of the public which can be distributed in mobile cloud computing. In this paper, we demonstrate that the public's shopping behavior of a commodity is a consequence of a collective behavior propagating through a social network and can be modeled as a simple ODEs model. Then, based on this new model, we develop an extended differential evolution algorithm that is deployed on mobile terminals and combined with the 5G network computing to estimate public incentives from historical sales datasets. The results suggest that this method can successfully monitor the public's purchase incentive. In addition, the overall purchase incentive changes dramatically during holiday seasons but fluctuates with similar patterns every year.

Keywords

• Mobile cloud computing
• Internet of Thing
• data analysis