Performance evaluation and Nash equilibrium of a cloud architecture with a sleeping mechanism and an enrollment service

Abstract

Cloud computing makes it possible for application providers to provide services seamlessly and application users to receive services adaptively. By offering services that give users an initial experience, application providers can usually attract more users. This research proposes a type of sleeping mechanism-based cloud architecture where an experience service and an enrollment service are provided on one virtual machine (VM). Accordingly, we model the cloud architecture as a queue with an asynchronous multi-vacation and a selectable extra service. We also analyze the queueing model in the steady state by constructing a three-dimensional Markov chain. Following this, we evaluate the system performance of the proposed cloud architecture based on the energy conservation level of the system and the mean delay of the visitors who select the enrollment service. Moreover, we study the Nash equilibrium strategy of visitors by building an individual welfare function, and develop an improved intelligent search algorithm to investigate the socially optimal strategy of visitors. Aiming to achieve a social optimum, we formulate a pricing policy with a reasonable enrollment fee.

Optimization of Intelligent Network Information Management System under Big Data and Cloud Computing

“…Jin, S. believes that the most precious information of mathematics in the data age is massive educational data, which is the core cornerstone of the development of intelligent education. Data mining technology and learning analysis technology are important fields under big data and cloud computing [5]. Moser, O. and others studied the management mode of big data discipline construction project with system engineering methodology, and put forward project man-agement suggestions from four dimensions [6].…”