# Programmable Data Plane Applications in 5G and Beyond Architectures: A Systematic Review
## 5 Open Points and Future Research Directions  
As programmable data plane implementations become increasingly relevant in 5G and beyond architectures, there are some open points and potential research directions that remain to be explored. Although there have been major advancements in research, a number of obstacles still need to be overcome. Within this section of the review, attention will be drawn to several critical domains that need further exploration, including issues corresponding to scalability, performance, computational constraints, interoperability, and energy efficiency. By identifying those gaps and future research tracks, the aim is to encourage further research in this emerging field. * Scalability: One of the main challenges associated with using programmable data planes in the 5G and beyond context is ensuring scalability to accommodate the large number of users and sessions these networks must manage. However, limited storage capacity on programmable devices poses constraints on state transfer, prompting further exploration of potential solutions. A promising approach is to use simultaneous software and hardware programmable devices, with the former managing low-traffic levels and the latter handling high-traffic levels. The study in [49] is a noteworthy approach that involves transitioning user connections to the hardware device if they exhibit high rates of data transmission. Additional studies that explore diverse hybrid software/hardware models can be found in [50; 58]. Another option for improving scalability is to incorporate a QoS scheduler within a programmable device to establish distinct queues, as proposed in [77]. Finally, a variation of multipath transport protocols such as QUIC could be employed to exploit available paths while minimizing data storage in intermediate nodes. A preliminary work on the compatibility of the aforementioned protocol with programmable devices is available in [105]. * Performance: Although programmable data planes have been effective in improving network throughput and reducing latency by offloading tunneling and forwarding of user plane data, challenges remain in optimizing the performance of 5G and beyond networks. Minimizing control plane intervention is desirable whenever possible. To this end, smart NICs offer the flexibility to manage complex user plane rules reducing control plane-user plane bottlenecks. The studies in [56; 65] can be seen as notable examples of leveraging the capabilities of smart NICs for optimization. Additionally, developing simpler control protocols can aid in offloading tasks to the data plane. The initial concepts of this approach are showcased in [57]. Another path for improving system performance is to explore end-to-end network slicing solutions that incorporate programmable devices in the NG-RAN and edge-to-core sections of the network. A starting point is the work in [82], which showcases network slicing in the fronthaul section of the system architecture. More research is required to thoroughly explore the potential advantages offered by such solutions. * Computational limitations: Programmable data plane devices have inherent constraints in performing complex computations, as they do not support floating-point arithmetic operations and can handle integer values only. As a result, network functionalities that rely on complex operations will not be supported. To tackle this issue, approximation algorithms can be utilized to trade off precision for improved network performance. An application-oriented implementation of an approximation scheme utilizing the longest prefix match for programmable devices calculations is demonstrated in [106]. Another possible solution is to assign non-supported computations to the control plane (e.g., general-purpose CPUs), which is capable of handling more complex operations, as in the scheme presented in [107]. Nevertheless, this methodology could potentially result in a rise in latency, which represents a prospective aspect to take into account in forthcoming research work.