## 2 Materials and Methods
### MK-Mediod Algorithm
#### 2.3.3 Collaborative Storage and Resolution based on Index Neighbor Structure
The reason is that, for the same LNMRS topology, the longest forwarding path from the master node to its users will always be found in any index neighbor structure as long as the number of resolution requests is large enough. LNMRS topologies of different sizes are randomly constructed according to the same latency rules, so the maximum latency from the users to the master node is slightly different for different topologies, and the larger the topology size, the more likely it is to traverse to a larger latency value. ## 4 Conclusions

In this paper, we address the problem of unbalanced storage load between layers in LNMRS by co-store mapping items of a higher level resolution node to lower level resolution nodes. We construct an index neighbor structure to find nodes for inter-layer collaborative storage, and model the index neighbor construction problem as a combinatorial optimization problem. We propose an index neighbor structure construction method based on our proposed MK-Mediod algorithm. Based on the constructed index neighbor structure, this paper propose an inter-layer collaborative storage and resolution method that satisfies the deterministic service delay feature. We compare the cost and effect of the index neighbor structure-based collaborative storage and resolution method in this paper with three other index neighbor construction algorithms. The results show that to co-store the same number of mapping records for the master node, the increase of total storage load is less when index neighbor structure constructed in this paper is used for collaborative storage, which is is 57.1% of that in the MGreedy algorithm, 8.1% of the Greedy algorithm, and 0.8% of the K-Mediod algorithm. The computation overhead in the construction procedure of our algorithm is only 3.73% of

Figure 9: Maximum resolution latency of each algorithm with different network sizes. that in the original K-Mediod algorithm, and the latency measurement overhead is the same as that in the original K-Mediod algorithm. Although Greedy and MGreedy algorithms have less latency measurement and computational overhead, their corresponding total storage load increase is too large in the collaborative storage procedure. It is worth noting that no matter which index neighbor structure is used for collaborative resolution, the deterministic service latency constraint of the master node is still sustained. Experiment results show that our proposed index neighbor structure-based collaborative storage and resolution method could achieve collaborate storage with less computation and storage cost compared with other algorithms. However, the proposed MK-Mediod algorithm has a limit that it must be executed centrally, which means a bad scalability. Future work can be considered in the following two aspects: First, the greedy algorithm can be executed distributively at each child node. However, the K-Mediod algorithm and the modified algorithm based on it need a complete latency measurement result for execution. How to perform the MK-Mediod algorithm distributively, supporting better scalability, should be considered. Second, we select one index neighbor in each index neighbor group in this paper, but there might be more than one node meeting the constraints of the index neighbor. It should be considered to maintain, as much as possible, the index neighbors in one index neighbor group for the sake of storage load balancing. Conceptualization, [PERSON] ([PERSON]) and Y.L. ([PERSON]); methodology, [PERSON] ([PERSON]) and [PERSON] ([PERSON]); software, [PERSON] ([PERSON]); writing--original draft preparation, [PERSON] ([PERSON]); writing--review and editing, [PERSON] ([PERSON]) and [PERSON] ([PERSON]); supervision, [PERSON] ([PERSON]); project administration, [PERSON] ([PERSON]); funding acquisition, [PERSON] ([PERSON]). All authors have read and agreed to the published version of the manuscript. This work was funded by the Strategic Leadership Project of Chinese Academy of Sciences: SEANET Technology Standardization Research System Development (Project No.