## 7 Discussion and Conclusions  
In this paper, a blockchain-based RSU cluster collaborative storage scheme was proposed to address the storage scalability issue in blockchain-enabled SloV. First, we introduced RAPSCA to tackle the RSU clustering problem, where RSUs were grouped into collaborative storage clusters based on block access preference similarity and resource conditions. Then, we designed VSPGBAA, which optimally allocated blocks to RSUs within each cluster by considering both the dwell time of vehicles and their block access probability. The proposed collaborative storage scheme effectively reduced the storage burden on individual RSUs while also optimizing the vehicle access cost introduced by the cluster-based architecture.  
Through simulation experiments, the proposed scheme has demonstrated robust optimization performance and high computational efficiency. It is important to acknowledge that the current validation was conducted in a simulation setting. Thus, the lack of real-world IoT device heterogeneity and dynamic network topology variations may limit the direct applicability of the findings. Future work will focus on validating the framework in edge computing environments that incorporate actual vehicular nodes. In addition, the following key research directions are identified for further investigation:  
1. Dynamic Cluster Adaptation: While the current RSU clustering assumes static networks, practical SloV requires mechanisms addressing vehicular mobility and load fluctuations. Future research will focus on developing an adaptive cluster reorganization mechanism that dynamically adjusts cluster membership based on real-time monitoring of storage utilization, inter-node latency, and blockchain query patterns.
2. Large-Scale Validation in Heterogeneous Edge Environments: The simulation-based evaluation will expand to physical testbeds combining heterogeneous edge devices and intermittent connectivity scenarios. Priority will be given to ultra-dense urban deployments where storage-consensus latency coupling impacts service reliability.
3. Storage-Consensus Co-Design: Building upon honest-but-curious assumptions, future research will formalize Byzantine-resilient storage strategies, particularly anti-collusion mechanisms against storage-aware Sybil attacks. This involves co-optimizing Proof-of-Storage parameters with cluster formation criteria to prevent adversarial coalitions without compromising access efficiency.  
Conceptualization, D.H. and K.P.; data curation, G.W.; investigation, L.W.; methodology, C.D.; resources, K.P.; software, J.H.; validation, L.W. and J.H.; writing--original draft, L.W. and X.L.; writing--review and editing, L.W. and L.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the Key Research and Development Program of Hubei Province under grant 2023 BAB074, in part by the Key Research and Development Program of Hubei Province under grant 2023 BAB074.  
Figure 8: Results of block allocation algorithms with the number of blocks.  
Province under grant 2024 BAB016, in part by the Key Research and Development Program of Hubei Province under grant 2024 BAB031.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors would like to thank [PERSON] (State Grid Hubei Information & Telecommunication Company) for her support in providing technical resources and infrastructural assistance for simulation and modeling. Her contributions to the experimental setup, access to internal platforms, and valuable insights during the review discussions are gratefully acknowledged.  
Authors [PERSON], [PERSON], [PERSON] and [PERSON] were employed by the company State Grid Hubei Information & Telecommunication Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.