Complexity and monitoring of economic operations using a game-theoretic model for cloud computing

Abstract

In this study, a model is presented for allocating cloud computing resources based on economic considerations using tools from game theory. The model, called the Non-Cooperative Game Resource Allocation Algorithm (NCGRAA), is designed to achieve the optimum stage in cloud computing. In addition, the Bargaining Game Resource Allocation Algorithm (BGRAA) is introduced to the existing system to develop the billing process within the constraints of availability and fairness. This system-based algorithm implements methods for converging on and improving the Nash Equilibrium and Nash Bargaining solutions. While the Nash equilibrium helps to develop decision-making concepts with game theory, one of its main goals is to achieve the desired outcome and avoid deviation from the working stage. Nash Bargaining is a unique solution that occurs between two parties and takes into account the process of bargaining to provide a fair solution that is scale invariant and independent. In recent years, cloud computing has become a popular way to manage computing services and enable producers and consumers to interact. This process allows users to obtain goods at an affordable cost from sellers according to their expectations. This research investigates the economic operation monitoring of cloud computing using the gaming theory model. A Static Negotiation Analysis Method with a Bargaining Process (SNAM-BP) for a dynamic conceptual framework is presented to display the weighted relationship between primary issues and keywords used to evaluate the potential partnership of each country.