区块链赋能的高效物联网数据激励共享方案

近年来，随着大量设备不断地加入物联网中，数据共享作为物联网市场的主要驱动因素成为了研究热点.然而，当前的物联网数据共享存在着出于安全顾虑和缺乏激励机制等原因导致用户不愿意参与共享数据的问题.在此背景下，区块链技术为解决用户的信任问题和提供安全的数据存储被引入到物联网数据共享中.然而在构建基于区块链的安全分布式数据共享系统的探索中，如何突破区块链固有的性能瓶颈仍然是一个关键挑战.为此，本文研究了基于区块链的高效物联网数据激励共享方案.该方案首先提出了一个高效的区块链物联网数据激励共享框架，称为ShareBC.ShareBC利用分片技术构建能够并行处理数据共享交易的异步共识区，并在云/边缘服务器上和分片异步共识区上部署高效的共识机制，从而提高数据共享交易的处理效率.然后，为激励物联网用户参与数据共享，提出了一种基于智能合约实现的层次数据拍卖模型的共享激励机制.该机制解决了物联网数据共享中涉及的多层数据分配有效性问题，能够最大限度地提高整体社会福利.最后，实验结果证明了该方案的经济效益、激励兼容性和实时性以及可扩展性，且具有较低的计算成本和良好的实用性.

Efficient Blockchain-empowered Data Sharing Incentive Scheme for Internet of Things

In recent years, with a large number of devices that continuously join the IoT, data sharing as the main driver of the IoT market has become a research hotspot. However, the users are reluctant to participate in data sharing due to the security concerns and lack of incentive mechanism in current IoT. In this context, blockchain is introduced into the data sharing of IoT to solve the trust problem of users and provide secure data storage. However, in the exploration of building a secure distributed data sharing system based on the blockchain, how to break the inherent performance bottleneck of blockchain is still a major challenge. For this reason, we studied the efficient blockchain-based data sharing incentive scheme for IoT, in which an efficient data incentive sharing framework based on blockchain was proposed, named ShareBC. Firstly, ShareBC uses sharding technology to build asynchronous consensus zones that can process data sharing transactions in parallel and deploy efficient consensus mechanisms on the cloud/edge servers and asynchronous consensus zones in sharding, thus improving the processing efficiency of data sharing transactions. Then, in order to encourage IoT users to participate in data sharing, a sharing incentive mechanism based on hierarchical data auction model implemented by smart contract is presented. The proposed mechanism can effectively solve the problem of multi-layer data allocation involved in IoT data sharing, and maximize the overall social welfare. Finally, the experimental results show that our proposed scheme is economically efficient, incentive-compatible, real-time, and scalability, and has low cost and good practicability.