A 3D-Collaborative Wireless Network: Towards Resilient Communication for Rescuing Flood Victims

Rahman, Arafatur; Hasan, M.M.; Asyhari, A. Taufiq; Bhuiyan, Zakirul Alam

doi:10.1109/dasc-picom-datacom-cyberscitec.2017.80

Cited by 13 publications

(8 citation statements)

References 29 publications

(23 reference statements)

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“…The average response of the node is often calculated when the terminal requests data. Then we use two A variety of different algorithms to compare the good or bad of this index, so as to measure the algorithm to some extent [26]- [28]. The specific corresponding data are shown in table 1.…”

Section: A Fog Computing and Cloud Computing Simulation Experimentsmentioning

confidence: 99%

Retracted: Cloud Network and Mathematical Model Calculation Scheme for Dynamic Big Data

Chen

Qiu

2020

IEEE Access

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Cloud network oriented to dynamics big data is a popular way of big data operation at present. It is a big data that can be applied to human behavior under dynamics. Time-based features include communication, network access and migration activities combined with unique physiological characteristics to complete big data. This paper aims to study a new cloud hybrid network architecture based on edge computing. This article uses this architecture to tectonic fog calculation layer between cloud servers and devices using edge devices such as communications and networks. After analysis, the obtained results are actively cached on the fog computing device and compared with the data of the telecommunication network detection terminal on the fog device. To consider the final result. The experimental data show that the distributed computing scheme can achieve the goal of minimizing the task processing delay. The experimental results show that the cloud network of the dynamic big data can meet the requirements of the contemporary big data completely, and the utilization ratio of the big data can reach 90%, and the calculation scheme of the mathematical model can run completely.

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Section: A Fog Computing and Cloud Computing Simulation Experimentsmentioning

confidence: 99%

Retracted: Cloud Network and Mathematical Model Calculation Scheme for Dynamic Big Data

Chen

Qiu

2020

IEEE Access

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“…By using this mesh topology, and intermediate nodes as relay points, ZigBee networks can increase their effective range past the 100 m limit. To be ideal for IoT devices with limited power capacity, ZigBee utilises low data rates, at 250 kbps, however a good portion of that transmission capacity is used for other functionalities (mesh protocol, transmission cryptographic security and acknowledgements) [83], [84].…”

Section: Proposed Smart Airport Architecturementioning

confidence: 99%

A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports

et al. 2020

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“…After pretraining, the DBN is fine tuned by marking samples. The fine-tuning process is described as follows: the output of the RBM in the last layer of the DBN is taken as the input of the back-propagation network and supervised by the backpropagation algorithm from back to front [31], [49]- [53].…”

Section: ) Fine-tuning Process Of the Dbnmentioning

confidence: 99%

Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

Tao

Zhang

et al. 2020

IEEE Access

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Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices. INDEX TERMS Dissolved gas analysis, power transformer, validity evaluation, empirical mode decomposition, deep belief network.

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A 3D-Collaborative Wireless Network: Towards Resilient Communication for Rescuing Flood Victims

Cited by 13 publications

References 29 publications

Retracted: Cloud Network and Mathematical Model Calculation Scheme for Dynamic Big Data

Retracted: Cloud Network and Mathematical Model Calculation Scheme for Dynamic Big Data

A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports

Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

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