Blockchain-Enabled Software-Defined Industrial Internet of Things with Deep Recurrent Q-Network
Recently, software-defined Industrial Internet of Things (SDIIoT), the integration of software-defined networking (SDN) and Industrial Internet of Things (IIoT), has emerged. It is perceived as an effective way to manage IIoT dynamically. Aiming to improve scalability and flexibility of SDIIoT, multi-SDN has been applied to form a physically distributed control plane to handle the large amount of data generated by industrial devices. However, as the core of multi-SDN, reaching consensus among multiple SDN controllers is a thorny issue. To meet the required design principle, this paper proposes a blockchain-enabled distributed architecture with SDIIoT to synchronize local views between distinct SDN controllers and finally reach the consensus of global view. On the other hand, both the cryptographic operations of blockchain and the noncryptographic computational tasks have access to the same computational resource pool of mobile edge cloud (MEC). In order to simultaneously optimize the throughput of blockchain and the energy consumption caused by computing, we adaptively allocate computational resources and the block size by jointly considering the trust features of SDN controllers and the resource requirements of non-cryptographic operations. To implement the truly distributed manner of blockchain, we describe our problem as a partially observable Markov decision process (POMDP) and propose a novel deep recurrent Q-network (DRQN) approach to solve it. In the simulation results, we compare two different protocols of blockchain and show the effectiveness of our scheme in either of them.
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|2020 IEEE International Conference on Communications, ICC 2020|
|Organisation||Department of Systems and Computer Engineering|
Luo, J. (Jia), Yu, F.R, Chen, Q. (Qianbin), & Tang, L. (Lun). (2020). Blockchain-Enabled Software-Defined Industrial Internet of Things with Deep Recurrent Q-Network. In IEEE International Conference on Communications. doi:10.1109/ICC40277.2020.9149217