# A Survey on Open Radio Access Networks: Challenges, Research Directions, and Open Source Approaches
## 6 Challenges and Future Research Directions
### Open RAN Field Issues
Additional scaling constraints will emerge if MNOs consider the use of accelerators. Furthermore, containerized orchestration alone cannot solve the high network availability and reliability operational goals. The applications will need additional built-in state synchronization and data integrity consideration. Moreover, specific failover and availability mechanisms will be required at the protocol level. 2. Most Open RAN enthusiasts assume that the architecture will bring significant economic savings while ignoring the cost of operating the complex architecture [89]. We have explained that a variety of new business roles are involved in the Open RAN ecosystem, such as the system integrator. The question is whether the service expense for these roles and OpEx in a multiword architecture at a large scale will exceed the cost-saving promised. The total TCO with large-scale operations is still undetermined [22]. 3. The gap between scalable automation and AI capability is another challenge to be considered [22]. The implementation of AI/ML technologies is relatively new in the telecommunication context. Using AI/ML in telecommunication grade operations will require significant resource expense. While interface standardization is currently available, data access, pipelines, and validation cannot be fully scaled due to a lack of standardized network configuration and performance data exchange. Furthermore, large-scale AI/ML asset deployment and operations by MNOs in live networks are still rare and complicated. To successfully scale and operate AI/ML use cases, harmonization of expertise from telecommunication, data science, and cloud/big-data fields is required [22]. OAI provides the Trirematics operator as a solution to answer the scalability challenge. Trirematics is an intelligent software operator for RAN and CN deployment scenarios [127]. Trirematics' orchestration and management framework is cloud-native and extensible. Trirematics include intelligence, agility, automation, abstraction, maintenance, and observability. Trirematics makes intelligent and agile decisions in deploying and operating the E2E network. It automates the lifecycle of the network entities and abstracts complexities in a 5G environment while providing enough diagnosis and control for its users. It also has extensive observability features, such as log processing, alerting, metric processing, and health monitoring. Rakuten Mobile's commercial deployment in Japan proves that Open RAN is ready for prime time. Dell'Oro Group's research report states that Open RAN is expected to acquire more than 10% of the RAN market share by 2025 [128]. While the majority respond enthusiastically, [5] view this result as proof to doubt the Open RAN adoption by the market. Whether these data and predictions are viewed positively or negatively is in the hands of each impacted party. Huawei clearly states that they do not support Open RAN or vRAN. Open RAN possesses many challenges, such as standardization, OpEx, and security issues that we have explained above. In addition, there might be political reasonsinvolved behind the Open RAN movement. This notion was researched, and Open RAN was considered a geopolitical hijacking case [129]. By considering Open RAN as a social imaginary of openness and trustworthiness, Open RAN can be weaponized to outcompete rivals by parties ranging from industry to government. Whether this is true or false is still debatable; hopefully, the truth will shine as time progresses.