A novel node selection scheme for energy-efficient cooperative spectrum sensing using D–S theory

Jin, Zilong; Qiao, Yu

doi:10.1007/s11276-018-1810-4

Cited by 3 publications

(1 citation statement)

References 34 publications

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“…The process of node participation in representative node selection or block generation is collectively referred to as consensus. The node reputation value comes from the performance of the historical consensus participation process and reflects the current status of the node as much as possible, that is, the more recent the consensus performance is, the greater the impact on the current reputation value [17]. In order to prevent the node reputation value from being too high and causing centralization, and to reflect the fluctuation of the node reputation value as much as possible, set the maximum credit value max of this node and obtain the i credit value R i of this node, as follows:…”

Section: Node Reputation Modelmentioning

confidence: 99%

Enhancing Global Blockchain Privacy via a Digital Mutual Trust Mechanism

Peng,

Zhu,

et al. 2024

Mathematics

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Blockchain technology, initially developed as a decentralized and transparent mechanism for recording transactions, faces significant privacy challenges due to its inherent transparency, exposing sensitive transaction data to all network participants. This study proposes a blockchain privacy protection algorithm that employs a digital mutual trust mechanism integrated with advanced cryptographic techniques to enhance privacy and security in blockchain transactions. The contribution includes the development of a new dynamic Byzantine consensus algorithm within the Practical Byzantine Fault Tolerance framework, incorporating an authorization mechanism from the reputation model and a proof consensus algorithm for robust digital mutual trust. Additionally, the refinement of homomorphic cryptography using the approximate greatest common divisor technique optimizes the encryption process to support complex operations securely. The integration of a smart contract system facilitates automatic and private transaction execution across the blockchain network. Experimental evidence demonstrates the superior performance of the algorithm in handling privacy requests and transaction receipts with reduced delays and increased accuracy, marking a significant improvement over existing methods.

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Section: Node Reputation Modelmentioning

confidence: 99%

Enhancing Global Blockchain Privacy via a Digital Mutual Trust Mechanism

Peng,

Zhu,

et al. 2024

Mathematics

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New probabilistic SINR analysis for capacity and reception-quality studies of DTV transmitter identification systems

Chang

et al. 2022

Wireless Netw

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Automatic Transmission Fault Symptom Identification by Apply of Neural Network and D-S Evidence Theory

O¹,

Chu

Sun

et al. 2021

IJSRST

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At present, the method of identifying the fault symptoms of various machines by combining the neural network and the D-S evidence theory is attracting attention from researchers because the identification time is fast and the diagnosis is accurate. In this paper, it was mentioned a method for identifying the fault symptoms of automatic transmission by combining these two theories. First, it was mentioned a method for identifying fault symptoms of the automatic transmission by combining a fuzzy neural network and an RBF neural network. Next, it was newly described a method to improve the accuracy of fault symptom identification by the D-S evidence theory. In addition, the accuracy of this method was verified by an experimental method. In the experiment Firstly, two sub neural networks are established to recognize the initial symptoms. That is, the first sub-neural network E1 be used as the fuzzy neural network, the second sub-neural network E2 be used as RBF neural network, respectively, for preliminary symptom recognition. And then, these outputs of the two sub neural networks are used as the evidence space of D-S evidence theory, so the global diagnosis is carried out. The results show that the test results are consistent with the actual fault symptoms. The success rate of fault diagnosis up to 96.3%, therefore, on the identification of the automatic transmission fault symptom, effectiveness, and feasibility of the D-S evidence theory based on information fusion is verified.

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A novel node selection scheme for energy-efficient cooperative spectrum sensing using D–S theory

Cited by 3 publications

References 34 publications

Enhancing Global Blockchain Privacy via a Digital Mutual Trust Mechanism

Enhancing Global Blockchain Privacy via a Digital Mutual Trust Mechanism

New probabilistic SINR analysis for capacity and reception-quality studies of DTV transmitter identification systems

Automatic Transmission Fault Symptom Identification by Apply of Neural Network and D-S Evidence Theory

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