# Adjacency-Information-Entropy-Based Cooperative Name Resolution Approach in ICN
## 4 Proposed Approach
### Latency Neighbor Maintenance
* Degree Priority (DP): This strategy considers the node with a larger degree and sends the request to the latency neighbors with the \(k\) largest degrees when selecting cooperative latency neighbors, and it is a basic baseline strategy. * Random Neighbor (RN): This strategy randomly selects \(k\) latency neighbors for forwarding during cooperative name resolution and is the easiest method to implement. The parameter \(k\) used in the DP, the RN, and the ACNR strategies is default, set as 4, and Section 5.3.3 further describes the tuning for this parameter. #### 5.3.1 Name Resolution Success Rate

To measure the performance of different latency neighbor cooperative name resolution strategies, the average name resolution success rate is used as an evaluation criterion. The overall name resolution success rate is one of the core metrics of an NRS. It represents the ratio of the number of name resolution requests successfully resolved in an NRS over a period of time to the total number of name resolution requests received by the system directly from users. The successfully resolved means that a name resolution node successfully queries



improve the resolution success rate, while the RN strategy only sends random requests without targeting, resulting in underutilizing the resolution capacity of neighbors. ACNR and DP take advantage of the connectivity of neighbors, thus effectively improving the name resolution success rate. As the speed of user requests increases, the number of name resolution requests and cooperative name resolution requests received by each name resolution node increases, and some hot name resolution nodes will gradually become overloaded due to the limitation of the nodes' computation, storage, or bandwidth resources, and cannot complete the higher concurrent volume of name resolution requests. So, the name resolution success rate will decrease. As shown in Figure 5, when the request rate reaches 50 K, the name resolution success rates of all strategies are at 27-31% with a small difference. Among the different strategies, the AN strategy will overload more name resolution nodes faster, thus its success rate decreases the fastest. The RN strategy, since it does not take into account any factors, makes the most balanced load on the name resolution nodes, so it has the slowest success rate decrease. Even when the request rate reaches a certain value, RN becomes the strategy with the highest success rate. Finally, we can see that ACNR has the most stable name resolution success rate regardless of the request rate variation, and it generally outperforms the DP strategy which only considers the node degree. The effectiveness of the ACNR method proposed in this paper is demonstrated. #### 5.3.2 Name Resolution Node Load

We notice that the name resolution success rate has a relationship with the distribution of request load by name resolution nodes in the NRS. With an inappropriate cooperative name resolution strategy, it can lead to an excessive load on some nodes, according to queuing theory and the long-tail effect. After exceeding the threshold value, the node will not be able to complete the local resolution in a limited time, and cannot complete the cooperative name resolution with other name resolution nodes. We measure the performance of each cooperative resolution strategy in terms of the total request load of the name resolution nodes and the standard deviation of the request load. Due to the relatively small number of high-level name resolution nodes and their latency neighbors, the variability across policies is not obvious, so we choose the bottom level to explore the request load characteristics. Figure 6a shows the total number of name resolution requests received by the NRS from users' name resolution requests and cooperative name resolution requests from other nodes under each strategy. It can be seen that the total number of name resolution requests increases as the user request rate increases for each strategy.