Tornado: Enabling Blockchain in Heterogeneous Internet of Things Through a Space-Structured Approach

被引:47
作者
Liu, Yinqiu [1 ]
Wang, Kun [2 ]
Qian, Kai [1 ]
Du, Miao [1 ]
Guo, Song [3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Internet Things, Nanjing 210003, Peoples R China
[2] Univ Calif Los Angeles, Dept Elect & Comp Engn, Los Angeles, CA 90095 USA
[3] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
来源
IEEE INTERNET OF THINGS JOURNAL | 2020年 / 7卷 / 02期
关键词
Blockchain; consensus mechanism; heterogeneity; Internet of Things (IoT); scalability; SCALABLE BLOCKCHAIN; INDUSTRIAL INTERNET; IOT; SYSTEM; OPTIMIZATION; MANAGEMENT;
D O I
10.1109/JIOT.2019.2954128
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the widespread applications of the Internet of Things (IoT), e.g., smart city, business, healthcare, etc., the security of data and devices becomes a major concern. Although blockchain can effectively enhance the network security and achieve fault tolerance, the huge resource consumption and limited performance of data processing restrict its deployments in IoT scenarios. Observing the heterogeneity and resource constraints, we intend to make blockchain accommodate both wimpy and brawny IoT devices. In this article, we present Tornado, a high-performance blockchain system based on space-structured ledger and corresponding algorithms, to enable blockchain in IoT. Specifically, we first design a space-structured chain architecture with novel data structures for promoting the network scalability. To address the huge heterogeneity of IoT, a novel consensus mechanism named collaborative-proof of work is developed. Moreover, we propose the space-structured greedy heaviest-observed subtree (S(2)GHOST) protocol for improving the resource efficiency of IoT devices. Additionally, a dynamic weight assignment mechanism in S(2)GHOST contributes to reflect the trustworthiness of data and devices. Extensive experiments demonstrate that Tornado can achieve a maximum throughput of 3464.76 transactions per second. The optimizations of propagation latency and resource efficiency are 68.14% and 30.56%, respectively.
引用
收藏
页码:1273 / 1286
页数:14
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