# Performance Analysis of Storage Systems in Edge Computing Infrastructures
## 5 Conclusions and Future Work  
The distributed and heterogeneous nature of the edge and its limited resource capabilities pose challenges in implementing or choosing an efficient edge storage system. In this work, we present an overview and a performance analysis of three different storage systems, namely MinIO, BigchainDB, and the IPFS. The effectiveness of each storage system is evaluated by employing a number of QoS and resource utilization metrics. Each storage system is deployed and installed on an RPi, which serves as an edge device, able to optimize the overall efficiency with minimum power and minimum cost. The experimental results demonstrated that MinIO yields the best performance in every setting while BigchainDB comes second in most cases. Furthermore, although the IPFS has a relatively low response time, it also exhibits a large variation in the response time between each operation, resulting in a high standard deviation from its average performance. Moreover, it is worth noting that the response times of each storage system are comparable to each other, and more workload and stress testing is required to further support the findings of our research.  
One of the fundamental requirements for bulk data processing in cloud and edge infrastructures is database scalability. Therefore, as future work, we plan to examine the scalability of the evaluated storage systems by deploying them in the distributed mode. As already mentioned, each system belongs to a different type of storage; therefore, the distributed mode differs significantly. For instance, MinIO in the distributed mode sets up a highly available storage system with a single-object storage deployment, while the IPFS Cluster provides data orchestration across a swarm of IPFS daemons by allocating, replicating, and tracking a global pinset distributed among multiple peers. In addition, BigchainDB creates a network with no single point of control/failure, and the decentralized control is operated via a federation of voting nodes composing a P2P network. Finally, we intend to consider some additional metrics for the evaluation, such as the input/output operations per second and cache hit ratio.  
[PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] worked on the conceptualization of the work. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] worked on the methodology and, with [PERSON], developed the final solution. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] worked on the experiments and the original draft preparation. [PERSON] helped with the writing--review and editing--of the final manuscript and performed the overall project supervision. All authors read and agreed to the published version of the manuscript.  
This research has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101016509 (CHARITY) and No. 871793 (ACCORDION). Furthermore, this work was supported the SmartShip Project through the European Union's Horizon 2020 research and innovation program under the Marie-Sklodowska Curie Grant Agreement No. 823916. The work reflects only the authors' view, and the EU Agency is not responsible for any use that may be made of the information it contains.  
Not applicable.  
Figure 4: Transaction rate achieved by each storage system.