# Programmable Data Plane Applications in 5G and Beyond Architectures: A Systematic Review
## 1 Introduction  
Programmable data planes have emerged as a critical component of modern networking architectures, enabling greater flexibility, faster processing, and more efficient use of network resources. Following the principles of software-defined networking (SDN) [1] in programmable data planes, the control plane and data plane are separated, allowing for more granular control over network traffic and enabling administrators to configure and adapt networks to changing requirements and traffic patterns.  
To enable programming of the data plane, a variety of programming languages have been developed throughout the years, each offering distinct attributes and functionalities, e.g., Domino [2], Lucid [3], NetKAT [4], OpenState [5], and P4 [6]. However, P4 (Programming Protocol-Independent Packet Processors) is the most widely used language in the state of the art. Furthermore, this language enables the creation of custom packet processing pipelines, allowing for the implementation of advanced features and services, such as traffic monitoring, load balancing, function offloading, and security filtering.  
The evolution of communication architectures, including the emergence of 5G and beyond [7], has created opportunities for SDN and programmable data planes to show their potential as key enabler technologies. These architectures handle vast amounts of users and their data, requiring rapid and effective processing to cater to a diverse array of applications and services [8]. SDN, in this context, offers architectural flexibility and scalability to address the complexities of managing a large number of connected devices. By utilizing centralized controllers, SDN simplifies management and automates tasks such asprovisioning, configuration, and troubleshooting within telecommunication network infrastructure. Its programmable and dynamic nature enables operators to swiftly reconfigure the network and allocate resources based on specific use case requirements [9]. Complementarily, programmable data planes can be used to support low-latency applications, such as autonomous vehicles or industrial automation, by providing fast and efficient pipelines. They could also be employed to provide higher throughput in user plane functions and help reach new levels of mobile broadband connectivity.  
The integration of programmable data planes in 5G and beyond architectures presents both advantages and potential impacts, but it also introduces implementation challenges. By offloading specific network function tasks to programmable devices, the overall network performance can be significantly optimized, thereby fulfilling the stringent requirements and key performance indicators (KPIs) of 5G and upcoming technologies [10; 11]. Moreover, the inherent customization capability of these devices enhance support for network slicing and multi-access edge computing, essential features in novel telecommunication systems. However, the deployment of programmable data planes poses challenges in efficiently managing a vast number of users, ensuring seamless communication between different vendor network devices, and overcoming the limitations of data plane programming languages for novel use cases. Despite these hurdles, programmable data planes have the potential to enable mobile networks to operate at optimal levels, thus enhancing user experience. Furthermore, they accelerate innovation cycles and enable experimentation, fostering the development of more advanced and transformative telecommunication networks.  
In the following subsections, the contribution of this review will be presented in detail along with its objectives and distinctive features compared to other reviews.