Cross-Domain Data Sharing for the Internet of Vehicles via a Dual-Layer Blockchain with Cross-Layer Asynchronous Validation and Reinforcement Learning -Based Scheduling

• ChengLin Chen,
• LeJun Zhang,
• Ran Guo,
• JuXia Li,

Vol. 20, No. 1, January 31, 2026
10.3837/tiis.2026.01.008, Download Paper (Free):

• Blockchain
• IoV
• Cross-domain Sharing
• Reinforcement Learning
• Asynchronous Validation

Abstract

The Internet of Vehicles (IoV) relies on seamless cross-domain data sharing to enable cooperative perception, real-time traffic management, and inter-regional service handover. However, challenges such as cross-regional ledger inconsistency, verification delays in resource-based edge nodes, and lack of flexible scheduling under dynamic workloads hinder data sharing. In order to solve these problems, we propose an integrated framework for asynchronous validation and adaptive scheduling. First, we proposed a dual-layer blockchain architecture, in which the regional shard chain achieves efficient intra-domain consensus, and the backbone chain ensures the consistency of cross-domain ledgers. Second, we design a cross-layer asynchronous verification (CLAV) mechanism to significantly reduce the verification delay by decoupling the local and global verification processes. CLAV also maintains high security with minimal computing overhead by combining lightweight elliptic curve cryptography (ECC) and smart contracts. Finally, we deploy a scheduler based on reinforcement learning in the urban data center (UDC) to realize the dynamic allocation of tasks and resources. Experimental evaluation shows that compared with the baseline method, our method can reduce the verification delay by up to 50%, increase the throughput by 15%, and reduce the average task delay by 20%. These improvements make it possible to have a scalable and secure Internet of Vehicles system for the smart city environment.

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