Efficient State Replication for Network Functions in Cloud Computing

One of the key challenges in managing network functions is their statefulness, which means they maintain information about the network’s current state. This information must be kept up-to-date and consistent across all NFs to ensure proper functioning. To address this challenge, researchers have proposed using a distributed computing and storage platform, such as Hazelcast, to manage stateful network functions.
Another challenge is the tight coupling between state and processing in NFs. This means that changes to the network’s state can have significant impacts on how the functions are processed. To break this coupling, researchers have proposed using stateless network functions, which separate state management from processing. This allows for more flexible and scalable network function management.
In addition to these approaches, researchers have also explored the use of caching objects locally for NFs that can tolerate stale data. By caching objects, NFs can reduce their reliance on remote resources and improve their overall performance.
Finally, replicating objects across NFs for eventual consistency is another important approach for managing network functions. This ensures that all NFs have access to the same information, reducing the risk of errors or inconsistencies.
In summary, managing network functions can be complex due to their statefulness and tight coupling with processing. However, by using distributed computing platforms, stateless network functions, caching objects locally, and replicating objects across NFs, these challenges can be addressed and improved network function management achieved.