In Industrial Internet of Things (IIoT), Peer-to-Peer (P2P) energy trading ubiquitously takes place in various scenarios, e.g., microgrids, energy harvesting networks, and vehicle-togrid networks. However, there are common security and privacy challenges caused by untrusted and nontransparent energy markets in these scenarios. To address the security challenges, we exploit the consortium blockchain technology to propose a secure energy trading system named energy blockchain. This energy blockchain can be widely used in general scenarios of P2P energy trading getting rid of a trusted intermediary. Besides, to reduce the transaction limitation resulted from transaction confirmation delays on the energy blockchain, we propose a credit-based payment scheme to support fast and frequent energy trading. An optimal pricing strategy using Stackelberg game for credit-based loans is also proposed. Security analysis and numerical results based on a real dataset illustrate that the proposed energy blockchain and credit-based payment scheme are secure and efficient in IIoT.

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It is desirable for alarm packets to be forwarded to the sink as quickly as possible in wireless sensor networks. In this paper, we initially analyze the theory of the relationships between network configurations and network lifetime as well as transmission delay. Then, we propose an approximate optimization approach to minimize the end-to-end delay with a reduced complexity of configuration under the condition that the network lifetime remains greater than the specified target value. A local forwarding approach named Fast data collection for nodes Far away from the sink and slow data collection for nodes Close to the Sink (FFSC) is proposed. This approach is energy efficient. Moreover, it can further reduce the end-to-end delay. Both the comprehensive theoretical analysis and the experimental results indicate that the performance of FFSC is better than the methods proposed by previous studies. Relative to the direct forwarding strategy, the FFSC approach can reduce the delay by 7.56%-23.16% and increase the lifetime by more than 25%. It can also increase the energy efficiency as much as 18.99%. Relative to the single fixed threshold strategy, the FFSC approach can reduce the delay by 4.16%-9.79% and increase the energy efficiency by 19.28% while still guaranteeing the same lifetime as those previous methods.

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