Modeling of a Software-Defined Reflective Intelligent Surface Network Using Queueing Theory

To enhance redundancy and ensure continuous connectivity in conventional communication systems, a method utilizing an on-demand forwarding signal transmitter enabled by a reflective intelligent surface (RIS) serves as a flexible and adaptive solution, particularly for outdoor communications. However, managing and regulating these RISs in dynamic environments present significant challenges, particularly in large-scale network systems. Software-defined networking presents a compelling method for managing networks in contrast to traditional networking, delivering automated, centralized, and intelligent control. In this paper, we introduce a software-defined RIS network architecture that aims to address the expected demands of future wireless communication, focusing on high network availability, the improved convergence of connectivity, and improved performance. The results of this study indicate that the achievable data rate is increased by approximately 35%, energy efficiency is improved by about 15%, packet processing time is nearly 2.32% shorter, server utilization is improved by approximately 48%, pathloss is minimized by roughly 64%, spectral efficiency is improved by nearly 84.2%, service rate is improved by approximately 38.7%, and packet arrival rate is exacerbated by approximately 3.3%.