Energy efficiency optimization of mobile edge computing e-commerce clients and reasonable management of server computing resources are worth further study. The participant of the algorithm game model proposed in this paper is mobile e-commerce customer management. The decision space is a two-dimensional space composed of unloading decision and power control, and the benefit function is the energy efficiency function and delay function. The existence and uniqueness of the multidimensional game model are proved theoretically. The simulation results show that the proposed multidimensional game based energy efficiency optimization algorithm of mobile edge computing can reduce the energy consumption and delay of mobile terminals and improve the energy efficiency of unloading calculation under the same task compared with the game scheme without considering power consumption control when the number of e-commerce customer management is larger. This paper deduces the optimal load migration decision of mobile e-commerce customer management and the optimal pricing strategy of mobile edge cloud service providers and proves that the optimal decision and optimal pricing constitute the Starkberg equilibrium. The semidistributed and decentralized task transfer decision-making mechanisms are designed, respectively, and the management decision-making behaviors of mobile e-commerce customers in the mobile edge cloud energy trading market are studied by numerical analysis, as well as the time efficiency of the two mechanisms.

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This paper proposes a SaaS (Software-as-a-Service) maturity model, and proposes an intelligent SaaS framework. The SaaS maturity has two dimensions. Traditional SaaS for business computing can also be extended to include intelligent behavior by having ontology to describe metadata of those data used in SaaS. Then, this paper proposed a new SaaS architecture SmartSaaS, and illustrate its key features. Finally, a conceivable architecture of implementation and technology roadmap were given.