Research On Profit Maximization Strategy Of Cloud Computing Based On Constraint

Science and technology service industry is one of the new service industries based on science and technology innovation.As an innovative modern service industry with intensive information and knowledge,the science and technology service industry are characterized by multiple features,such as its close linking to human intelligence and advanced technology,huge additional value in industry and strong radiation effect of science and technology.However,currently it is still difficult to quantify its value increment process directly and promptly.Therefore,it is a meaningful value to explore the specific phases,extensions and related models of the value increment process of science and technology service industry,as well as to develop a method to quantify the value of science and technology resources services.In recent years,a typical application of science and technology services----cloud services have attracted enormous attention.In cloud services,cloud computing is a big data operation platform.Through the centralized management of resources and services,cloud computing provides hosting services through the Internet,which provide cost-effective aggregated computing resources to consumers on demand from the basic information resources from its rental accesses.In this paper,a class of service splitting issues are first proposed.Considering that each task consists of several subtasks in logical order,each subtask corresponds to a service request type that can be provided in a unique multi-service desk system.In addition,a constraint of customers’ waiting time is set to indicate the maximum waiting time that the customer can tolerate.Therefore,a key problem that the service intermediary is facing is how to configure the parameters of a multi-level multiservice desk queueing system in order to maximize profits and meanwhile to reduce customers’ waiting time.To address this problem,we first discuss the probability distribution function of the waiting time of a multilevel multi-service desk queueing system,and then innovatively develop a profit maximization model under a deadline constraint.Considering the complexity of this model,we utilize algorithmic optimality seeking.Finally,we conduct a series of numerical simulations of the proposed profit maximization scheme,the results of which demonstrate that our scheme not only maximizes profit but also effectively reduces the customers’ waiting time.To further explore the practicality of the model,we include the impact of price on the profit.In reality,customers not only expect the service to be completed but also require the estimated unit price of the service.In Chapter 3,We study not only the impact of service unit price on the customer arrival rate,but also the impact of the deadline constraint on service unit price are studied.In addition,a heuristic algorithm is applied to estimate the equilibrium point between its service completion and service brokerage revenue.The results show that our approach can identify the optimal equilibrium point between service completion and service brokerage revenue within the deadline constraint and a certain range of service unit price.Finally,the full research is summarized and analyzed,and a few insights are provided for feasible studies in the future.