Data Loss Transmission in 5g Network by Enabling Green Blockchain Methodologies

Abstract

Network embedding successfully maintains the network structure by assigning network nodes to low-dimensional representations. A considerable amount of progress has recently been achieved in the direction of this new paradigm for network research. In this study, we concentrate on classifying, analyzing, and pointing out the future direction for network embedding techniques to research. We begin by summarizing the purpose of network embedding. We talk about network embedding and how it relates to traditional graph embedding methods in a cognitive radio context. Following that, we give a thorough overview of the network embedding techniques methodical way, including advanced information-preserving network embedding techniques, network embedding techniques with side information, and approaches that preserve structure and properties. Additionally, many methods of network embedding assessment and some practical online tools, such as network data sets and software, are explored. In the last section, we cover the foundation for utilizing these network embedding techniques to create a successful system and identify possible future paths.