# Mathematical Models for Named Data Networking Producer Mobility Techniques: A Review
## 3 Recent Mobility Techniques
It is compatible with various NDN-related scenarios, including precise and comprehensive implementation of the NDN protocol and integration into ns-3 for authentic network simulations. On the other hand, OMNeT++ is a framework for simulating discrete events, and the INET framework expands its capabilities to simulate networking protocols. Existing simulation frameworks may have difficulties simulating large-scale NDN networks due to computational and memory constraints and presenting restrictions. The restricted scalability could impede the evaluation of NDN performance in situations involving many nodes and elements of content. Hence, simulations may need help in correctly capturing the intricate and dynamic nature of real-world networks. Simulation results may not adequately represent the challenges and complexities of NDN implementation in dynamic, heterogeneous contexts. Subsequently, specific simulation frameworks may need more complete implementation of all developing NDN protocol stack components. There needs to be more implementation of the protocol to allow for the investigation of specific scenarios and characteristics pertinent to the most recent advancements in NDN. Simulating NDN protocols may result in increased overhead, which can affect the precision of the simulation outcomes. Therefore, the outcomes derived from simulations may not accurately reflect the actual performance of NDN in real-world implementations. Particular requirements for accessing data in NDN efficient mechanisms enable consumers to access material from producers in a content-centric manner. To evaluate the effectiveness of NDN in delivering requested material, simulation frameworks must precisely replicate content retrieval scenarios, as well as efficient caching mechanisms for evaluating the influence of caching on latency reduction and network resource optimization. Simulation frameworks should offer comprehensive models for caching strategies, encompassing probabilistic, collaborative, and adaptive policies. Dynamic network conditions are modeled to evaluate NDN's ability to respond to changes in topology, producer mobility, and fluctuating demand patterns. Simulations should include scenarios with changing conditions to assess the resilience and agility of NDN. Constraints and disadvantages in regard to using ns3, OMNeT++, and ndnSIM while enacting NDN simulations: Simulating extensive NDN scenarios can provide difficulties regarding computational resources and memory use. The limited scalability of NDN may hinder evaluating its performance in cases involving many nodes and intricate network topologies. Simulations conducted with NS-3, OMNeT++, and ndnSIM can be computationally demanding, necessitating substantial computer resources and memory. Moreover, the computational limits of practicality may restrict the scale and complexity of experimentsthat can be undertaken due to the high resource requirements of simulations. The learning curve for these simulation tools is relatively high, particularly for users unfamiliar with simulation environments or lacking network simulation experience. Other than that, the learning curve may impede the acquisition of these technologies, especially for academics or practitioners with simulation competence. The level of NDN protocol implementation in simulation tools can vary, and certain features or parts of the protocol may need to be adequately depicted. Note that insufficient protocol support may restrict the investigation of particular scenarios or characteristics pertinent to the most recent advancements in NDN. The design and architecture of simulation tools may incorporate biases or assumptions that impact the authenticity of the simulated scenarios. Biases have the potential to affect the applicability of simulation findings and may not accurately capture the complexities of actual NDN deployments. Simulations conducted using NS-3, OMNeT++, and ndnSIM have the potential to operate at a significantly accelerated pace compared to real-time.