Hyperledger Fabric (Fabric for short), is a consortium blockchain platform that adopts the smart contract paradigm and provides complete operational functions. Although it has become the system with the highest throughput among open source blockchain systems, its performance cannot meet the needs of industrial-grade application scenarios. To further expand the application scenarios of blockchain, this paper proposes a Transaction Batch Processing Scheduling (TBPS) algorithm for multi-channel Fabric networks based on Lyapunov optimization theory. The algorithm maximizes the consensus efficiency of the system while ensuring the minimum transaction accumulation, and provides stability conditions and optimal performance for the system under transaction batch processing. Finally, we built a blockchain network of Fabric’s latest stable version v 2.0 via the cloud platform, providing an order of magnitude of algorithmic parameters by testing transaction processing rates. To simulate the distribution of performance indicators such as transaction delay, system transaction accumulation and average transaction processing rate under different impact factors, and verify the effectiveness of the proposed TBPS algorithm.

In this paper, we consider a novel covert communication scenario where the warden does not have prior knowledge of the transmitter’s power. In this scenario, the current widely adopted likelihood ratio test (LRT)-based detector is not optimal anymore. To address this, we formulate a detection framework based on the generalized likelihood ratio test (GLRT), which replaces the unknown parameter with maximum likelihood estimation (MLE) and is proven optimal in the scenario. Based on the GLRT-based framework, two different detection models are proposed, where one only utilizes observations of the current time and the other can exploit observations of past time slots. We analyze the estimation and fisher information of the transmit power, and even the detection and covert performance under two different detection models, respectively. Based on the analytical results, we further derive the maximum number of tolerable slots under which the transmitter can remain the same transmit power while the detection error probability of the warden is still larger than the regulated threshold. Moreover, the transmit power and the number of tolerable slots are jointly optimized to maximize the transmission throughput subjecting to covertness constraint. The numerical results demonstrate the correctness of the theoretical analysis. We show how the covert rate is influenced by the number of transmitting slots and the transmit power, which can guide the design of the covert transmission strategy.