# Comparative Analysis of Producer Mobility Management Approaches in Named Data Networking
## 2 Related Work
### Which NDN Producer MM Approach Is Best Suited for Latency-Sensitive Applications?  
Since a \"one-solution-fits-all\" method was not built-in for the producer MM in the original NDN design, there is no agreed upon approach that eliminates all possible disadvantages and meets all performance measures.  
As discussed above, each producer MM approach retains some advantages and other disadvantages. Nevertheless, precise evaluation of MM schemes should be considered in the context to which it is intended for. The context includes, for instance, a specific network topology, the application the nodes are running, and the mobility pattern of the nodes. Furthermore, in [43], the authors identified 12 factors that affect the performance of an MM scheme, such as changes in name prefixes and in-network caching.  
Additionally, different evaluation metrics were targeted in the literature to determine the achieved performance of the proposed schemes. Therefore, different approaches may enhance specific performance metrics at the cost of others.  
Therefore, in this study, we aim to find the best producer mobility management approach to efficiently accommodate the ever-increasing latency-sensitive traffic. This class of latency-sensitive applications requires more stringent performance requirements in terms of reduced data packet loss and data delivery delay.  
Hence, we analyze and compare three promising producer MM schemes, each representing a different approach. As followed in the conducted literature review in Section 2, we classified producer MM schemes into four approaches: routing, RV, proxy, and-data plane approaches.  
The selection of the three schemes was based on their representation of the intended approach, their reported efficiency performance, and the sufficient description of their design in the published work, which allowed us to implement them in NdnSIM.  
In our study, among the routing-based approaches, we chose adaptive forwarding-based link recovery for mobility support (AFIRM) [42]. The main idea is to recover request paths by updating the forwarding information after mobility detection.  
We choose Map-Me [32] as a representative of the data plane-based approaches. The main idea in Map-Me is allowing interests to follow the micro-level mobility of a mobile producer to enable faster reach and hence minimize delay.  
Due to the similarity between RV- and proxy-based solutions, which both fall under the anchor-based category, we chose Kite [26] as a representative of the anchor-based approaches in general. This similarity is seen in the basic design concept requiring an entity with a special role and the similarity in their design advantages and disadvantages, as summarized in Table 1. The main idea in Kite is to create a hop-by-hop trace between a stationary anchor and a mobile producer.  
We compare the three schemes under the stringent requirements of delay-sensitive streaming applications. To the best of our knowledge, there exists no previous work that implemented these three schemes in NdnSim and conducted a comparative analysis between them.  
In the following section, we describe the design of each scheme in detail.