With the popularity of the Internet of Things (IoT), data integrity verification in the edge cloud storage attracts attentions from many researchers. Due to the over dependence of the Third Party Auditor (TPA) and the dynamical nature of the IoT data, the traditional data integrity verification framework for cloud storage can hardly work. To satisfy the characteristics of the IoT and avoid the over dependence of the TPA, we propose a blockchain-based framework without TPA for data integrity verification in a decentralized edge-cloud storage (ECS) scenario in this paper. In our framework, we employ the Merkle tree with random challenging numbers for data integrity verification and analyze different Merkle tree structures to optimize the system performance. To solve the problem of limited resources and high real-time requirements, we further propose sampling verification and develop rational sampling strategies to make sampling verification more effective. The overhead and precision of the verification in ECS are studied by an optimal sample size strategy. Finally, a prototype system is implemented based on our framework. We conduct a series of experiments to evaluate the effectiveness of the proposed schemes. The experimental results show that our schemes can effectively improve the performance of data integrity verification.

随着物联网（IoT）的普及，边缘云存储中的数据完整性验证吸引了许多研究人员的关注。由于第三方审计师（TPA）的过分依赖和IoT数据的动态性质，传统的云存储数据完整性验证框架几乎无法工作。为了满足物联网的特性并避免TPA的过度依赖，我们在本文中提出了一种基于区块链的无TPA框架，用于在分散式边缘云存储（ECS）场景中进行数据完整性验证。在我们的框架中，我们使用带有随机挑战数的Merkle树进行数据完整性验证，并分析不同的Merkle树结构以优化系统性能。为了解决资源有限和实时性要求高的问题，我们进一步提出了抽样验证并制定合理的抽样策略，以使抽样验证更加有效。通过最优样本量策略研究了ECS中验证的开销和准确性。最后，基于我们的框架实现了原型系统。我们进行了一系列实验，以评估所提出方案的有效性。实验结果表明，该方案可以有效提高数据完整性验证的性能。我们进行了一系列实验，以评估所提出方案的有效性。实验结果表明，该方案可以有效提高数据完整性验证的性能。我们进行了一系列实验，以评估所提出方案的有效性。实验结果表明，该方案可以有效提高数据完整性验证的性能。