The applications of nature-inspired meta-heuristic algorithms for decreasing the energy consumption of software-defined networks: A comprehensive and systematic literature review

In the past ten years, networking experts have been more concerned about the rising energy consumption of communication networks. The software-defined networks approach is a way to make diverse and complicated network topologies simpler, more manageable, more adaptable, and more effective, including wireless body area networks. In order to streamline network administration, save operational costs, and promote innovation, software-defined networks are emerging as a new networking architecture that separates the data plane from the control plane. However, despite the importance of this issue, so far, no bibliometric study has been done on this issue. Hence, this study aims to use methods drawn from nature to optimize power usage in software-defined networks. Additionally, a thorough and original categorization of energy-efficient solutions has been offered. During the bibliographic review, the sections of interest of researchers and some bibliographic information in the form of statistical information are expressed. Therefore, searching and selecting relevant keywords are done using the VOSviewer tool. The data is extracted from valid databases. Guidelines for future research on softwaredefined networks are derived based on the existing research projects' findings and the gaps and constraints that have been found. The results showed that the algorithms inspired by nature were successful in striking a balance among resource usage, energy consumption, and network performance.