LDC: A lightweight dada consensus algorithm based on the blockchain for the industrial Internet of Things for smart city applications
Introduction
A smart city is a concept of using sensors and data collection in cities to improve services using many Internet of Things (IoT) technologies. Many cities, communities, and municipal governments are looking to smart city technology as the next evolution of e-governance, enabling new interactions with the public or reducing the overhead of existing policies [1]. As an important part of a smart city, the smart factory is a new stage in the development of modern factory information. The smart factory or digital factory uses the IoT and equipment monitoring technology to strengthen information management and service [2], enhance production and marketing, improve the controllability of the production process, reduce manual intervention on the production line, timely and correctly collect production line data, and design production plans and production schedules [3]. In addition, intelligent green systems and other emerging technologies are integrated to build a high-efficiency, energy-saving, and green factory [4]. The industrial Internet of Things (IIoT) is an IoT-enabled industrial production system that provides improvements in efficiency and economic benefits related to system installation, maintainability, scalability, and interoperability [5].
The IIoT is experiencing exponential growth in research and industry, although privacy issues and security vulnerabilities are ongoing problems [6], [7]. The deterministic nature, reliability, and real-time application of data communication have always been a challenge for practical applications in the industrial field [8]. Due to the complex environment of industrial sites, multi-hop transmission is usually used for data collected by the sensor nodes of the IIoT to achieve long-distance transmission, causing unpredictable consequences, such as network transmission interruption or data loss due to noise, interference, and signal interruption [9]. In addition, the deployment environments of the IIoT are usually unattended and lack network security measures. Access to sensor nodes can, therefore, be easily gained by enemies, and malicious attacks can occur, such as eavesdropping or destroying and altering received messages [10]. Malicious attacks on nodes often result in data loss or confusion in network communication. Network managers receive incorrect data, which adversely affects the safety of industrial production [11]. It is evident that research on the reliability and accuracy of IIoT data is becoming increasingly urgent [12].
The application of blockchain technology to the IIoT has become a research hotspot. A blockchain is a distributed database or distributed ledger that is jointly created and maintained by multiple nodes [13]. Blockchain technology uses cryptography to prevent the forgery of and tampering with the block data, thereby solving the problems of low security, poor reliability, and high cost associated with the traditional centralized model. Due to the decentralized approach, traceability, and inability of tampering with the data, the use of blockchain technology in the IIoT guarantees the accuracy of data and provides a new direction for secure data transmission in the IIoT [14].
In this study, we use a network structure of multiple edge gateways for the IIoT and a lightweight data consensus (LDC) algorithm to ensure the accuracy and reliability of the data and the security of the network.
The main contributions of this study are as follows:
- (1)
A distributed ledger on multiple edge gateways is proposed, and all edge gateways record, synchronize, and maintain the ledger.
- (2)
We establish a lightweight data block structure, which saves storage space and resources, and we propose the LDC algorithm for the IIoT.
The rest of this paper is organized as follows. Section 2 describes relevant work related to the IIoT and blockchain. Section 3 presents the LDC algorithm based on the blockchain designed for the IIoT for a smart city application. The simulation results and performance analysis are discussed in Section 4. Section 5 provides the conclusion.
Section snippets
Related work
Security and privacy in the communication between IoT devices have been researched extensively in recent years. Blockchain technology represents a new application in IIoT systems, and its efficient implementation has been a subject undergoing intense study. The decentralized control, immutability, cryptographic security, fault tolerance, data integrity and authentication, and smart contracts of the blockchain are desirable features for the IIoT [15], [16]. Makhdoom et al. [17] discussed the
Network model
In the traditional IIoT, the perceptual information of thousands of IIoT device nodes is transmitted to a unique edge gateway. If the edge gateway fails, the entire network will be affected. The network structure of multiple edge gateways is stable, which minimizes network transmission interruption caused by the failure of a single edge gateway. This approach also prevents energy loss caused by the rapid exhaustion of the IIoT device nodes near the edge gateway and reduces the distance and
Simulation and analysis
The proposed LDC algorithm is verified using simulation experiments. The simulation parameters are listed in Table 1.
Six device nodes were randomly selected, and the average hop counts of these nodes to the edge gateways are shown in Fig. 7. The average hop count of the device node to the edge gateway is largest for the single edge gateway; this network structure has a large transmission delay and large network energy consumption. After the use of the clustering algorithm, the cluster head is
Conclusion
In this paper, we proposed the LDC algorithm based on blockchain technology using multiple edge gateways; the method was designed for use in the IIoT in a smart factory in a smart city application. The algorithm uses a distributed ledger on multiple edge gateways. The transmission strategy with dual-path routing provides data consistency during data transmission. The lightweight data block structure is an improvement over the traditional blockchain technology. The simulation results showed that
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The work is supported by the National Key Research and Development Program, China (No. 2017YFE 0125300), the National Natural Science Foundation of China-Guangdong Joint Fund under Grant (No. U1801264), the Jiangsu Key Research and Development Program, China (No. BE2019648), Liaoning BaiQianWan Talents Program (2016), China, Natural Science Foundation of Liaoning Province, China Project (No. 20170540793).
Wenbo Zhang is currently a professor of School of Information Science & Engineering, Shenyang Ligong University, China. He received his Ph.D. in Computer science at Northeastern University, China, in March 2006. He has published over 100 papers in related international conferences and journals. He has served in the editorial board of up to 10 journals, including Chinese Journal of Electronics and Journal of Astronautics. He had been awarded the ICINIS 2011 Best Paper Awards and up to 9 Science
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Wenbo Zhang is currently a professor of School of Information Science & Engineering, Shenyang Ligong University, China. He received his Ph.D. in Computer science at Northeastern University, China, in March 2006. He has published over 100 papers in related international conferences and journals. He has served in the editorial board of up to 10 journals, including Chinese Journal of Electronics and Journal of Astronautics. He had been awarded the ICINIS 2011 Best Paper Awards and up to 9 Science and Technology Awards including the National Science and Technology Progress Award and Youth Science and Technology Awards from China Ordnance Society. His current research interests are Ad hoc networks, Sensor Networks, Internet of things, Information Centric Networking.
Zonglin Wu received the B.S. degree in computer science and technology from Shenyang Ligong University, China, in 2018. She is currently pursuing the master’s degree with the school of Information Science and Engineering, Shenyang Ligong University, China. Her current research interests include Internet of things and underwater acoustic sensor networks.
Guangjie Han is currently a Professor with the Department of Information and Communication System, Hohai University, Changzhou, China and a Distinguished Professor of Dalian University of Technology, Dalian, China. He received the Ph.D. degree from Northeastern University, Shenyang, China, in 2004. In February 2008, he finished his work as a Postdoctoral Researcher with the Department of Computer Science, Chonnam National University, Gwangju, Korea. From October 2010 to October 2011, he was a Visiting Research Scholar with Osaka University, Suita, Japan. From January 2017 to February 2017, he was a Visiting Professor with City University of Hong Kong, China. He is the author of over 330 papers published in related international conference proceedings and journals, including the IEEE JSAC, IEEE COMST, IEEE TMC, IEEE TIE, IEEE TII, IEEE TCC, IEEE TPDS, IEEE TVT, IEEE IoT Journal, IEEE Systems, IEEE Wireless Communications, IEEE Communications, IEEE Network, etc., and is the holder of 130 patents. Currently, his H-index is 34 and i10-index is 102 in Google Citation (Google Scholar). Total citation of his papers by other people is more than 5030 times. His current research interests include Internet of Things, Industrial Internet, Machine Learning and Artificial Intelligence, Mobile Computing, Security and Privacy.
Dr. Han has served as a Co-chair for more than 50 international conferences/workshops and as a Technical Program Committee member of more than 150 conferences. He has served on the Editorial Boards of up to 16 international journals, including the IEEE JSAC, IEEE Network, IEEE Systems, IEEE ACCESS, IEEE/CCA JAS, Telecommunication Systems, etc. He has guest edited a number of special issues in IEEE Journals and Magazines, including the IEEE Communications, IEEE Wireless Communications, IEEE Transactions on Industrial Informatics, Computer Networks, etc. He has served as a Reviewer of more than 60 journals. He had been awarded the ComManTel 2014, ComComAP 2014, Chinacom 2014 and Qshine 2016 Best Paper Awards.
Yongxin Feng received the M.S. degree in Computer Science from Northeastern University in 2000, and the Ph.D. degree in Computer Science & Technology from the School of Information Science & Engineering, Northeastern University 2003. She is currently a professor in Shenyang Ligong University. She has published over 60 papers in related international conferences and journals. She had been awarded the ICINIS 2011 Best Paper Awards and up to 15 Science and Technology Awards including the National Science and Technology Progress Award and Youth Science and Technology Awards from China Ordnance Society. Her research interests are in the areas of Network Management, Wireless Sensor Network, Communication and Information Systems