 Categorizeing existing approaches along with their features exposes promising techniques and future directions' suggestions.  This work surveys and categorizes existing load balance, routing, and congestion solutions.  The investigated metrics of previous works are statically analyzed so as to highlight the most important factors that should be evaluated.  Enhancing network performance and AIbased approaches are the highest investigated topics in the last 6 years.High traffic could result in load imbalance or network congestion, which degrades the network's performance and efficiency. Thus, it is crucial to adopt efficient routing and load balancing models to face these challenging issues.Additionally, when investigating a new approach, it is essential to consider the most important metrics to evaluate this potential approach precisely. This paper presents an intensive analysis of recently available SDN-based load balancing and routing techniques. Furthermore, the features and issues of each technique are stated. Moreover, the most important metrics that should be evaluated are statically analyzed. Also, a brief survey of available network congestion solutions is shown. Additionally, taxonomies of available load balancing, routing techniques, and congestion solutions are presented. Finally, we shed light on the trends, promising techniques, and future directions' suggestions that could be utilized further in research. Investigating SDN-based research published by wellknown academic publishers in the last six years shows that enhancing network performance and AI-based approaches are the highest investigated topics with 28% and 27%, respectively, of the total investigated issues. Other topics took lower percentages. As far as we know, this study is the first work that jointly surveys and categorizes all existing approaches in the field of decreasing delay and congestion in SDN-based networks