A sharding blockchain-based UAV system for search and rescue missions

doi:10.1007/s11704-024-3467-8

Front. Comput. Sci.

2025, Vol. 19

Issue (3) : 193805 https://doi.org/10.1007/s11704-024-3467-8

Information Security

A sharding blockchain-based UAV system for search and rescue missions

Xihan ZHANG¹, Jiashuo ZHANG¹, Jianbo GAO^1,²(

), Libin XIA¹, Zhi GUAN³, Hao HU⁴, Zhong CHEN^1,²

¹. School of Computer Science, Peking University, Beijing 100871, China
². Peking University Chongqing Research Institute of Big Data, Chongqing 401329, China
³. National Engineering Research Center for Software Engineering, Peking University, Beijing 100871, China
⁴. State Key Lab for Novel Software Technology, Nanjing University, Nanjing 210023, China

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Abstract

Sharding is a promising technique to tackle the critical weakness of scalability in blockchain-based unmanned aerial vehicle (UAV) search and rescue (SAR) systems. By breaking up the blockchain network into smaller partitions called shards that run independently and in parallel, sharding-based UAV systems can support a large number of search and rescue UAVs with improved scalability, thereby enhancing the rescue potential. However, the lack of adaptability and interoperability still hinder the application of sharded blockchain in UAV SAR systems. Adaptability refers to making adjustments to the blockchain towards real-time surrounding situations, while interoperability refers to making cross-shard interactions at the mission level. To address the above challenges, we propose a blockchain UAV system for SAR missions based on dynamic sharding mechanism. Apart from the benefits in scalability brought by sharding, our system improves adaptability by dynamically creating configurable and mission-exclusive shards, and improves interoperability by supporting calls between smart contracts that are deployed on different shards. We implement a prototype of our system based on Quorum, give an analysis of the improved adaptability and interoperability, and conduct experiments to evaluate the performance. The results show our system can achieve the above goals and overcome the weakness of blockchain-based UAV systems in SAR scenarios.

Keywords blockchain sharding unmanned aerial vehicle search and rescue blockchain interoperability

Corresponding Author(s): Jianbo GAO

Just Accepted Date: 03 April 2024 Issue Date: 07 June 2024

Cite this article:

Xihan ZHANG,Jiashuo ZHANG,Jianbo GAO, et al. A sharding blockchain-based UAV system for search and rescue missions[J]. Front. Comput. Sci., 2025, 19(3): 193805.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-024-3467-8
https://academic.hep.com.cn/fcs/EN/Y2025/V19/I3/193805

Tab.1 Comparison of our system and existing systems

Fig.1 A schematic diagram of the search and rescue scenario. UAVs in the gray, red, and blue boxes represent that they are connected to the main chain, search shard, and rescue shard, respectively. Note that the red and blue boxes are inside the gray box, meaning that all members of the search or rescue shard are also connected to the main chain

Fig.2 A schematic diagram of automated creating shard process. The upper half shows the workflow on the main chain, where creation request is the output of

C t r g

generating process and the bond between the on-chain part and the off-chain part. The lower half shows the workflow on each UAV (off-chain). A process with a specific color represents that this process depends on the field with the corresponding color in the request, e.g., the yellow process shows that parameters of the contracts in

g e n e s i s

are set based on

c o n t r a c t s_p a r a m s

field in the request. Patterns and rules means these processes are pluggable modules that can be set up and replaced based on real-time surrounding situations

Fig.3 Workflow of cross-shard interaction on sending side

Fig.4 Data structure of cross-shard request

Fig.5 Workflow of cross-shard interaction on receiving side

Fig.6 Latencies of

L g

and

L c

with varying main chain nodes and shards. (a) Latency for generation; (b) latency for creation

Fig.7

Fig.8 Evaluation of system’s scalability from: the throughput and latency of transactions with varying nodes. Transaction payload size is set to 1 KB

Fig.9 Evaluation of system’s scalability from: (a) the throughput improvement rate with varying transaction complexity; (b) the comparison of throughput with and without sharding

Fig.10

Fig.11 Latency of a complete sharding process in 3 sharding approaches

Fig.12 Latency per phase for a single cross-shard request

Fig.13

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