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Jiangtao Luo

Researcher at Chongqing University of Posts and Telecommunications

Publications -  28
Citations -  500

Jiangtao Luo is an academic researcher from Chongqing University of Posts and Telecommunications. The author has contributed to research in topics: Computer science & Network packet. The author has an hindex of 7, co-authored 22 publications receiving 253 citations.

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Making Big Data Open in Edges: A Resource-Efficient Blockchain-Based Approach

TL;DR: A blockchain-based big data sharing framework to support various applications across resource-limited edges by exploiting blockchain’s non-repudiation and non-tampering properties that enable trust is developed.
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Energy-Balanced Unequal Layering Clustering in Underwater Acoustic Sensor Networks

TL;DR: The EULC algorithm designs UASNs with unequal layering based on node depth, providing a solution to the “hot spot” issue through the construction of clusters of varying sizes within the same layer.
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Cluster Frameworks for Efficient Scheduling and Resource Allocation in Data Center Networks: A Survey

TL;DR: A solid starting ground and comprehensive overview in this area is presented to help readers quickly understand state-of-the-art technologies and research progress and analyze desirable properties of fault tolerance and scalability to illuminate the design principles of distributed systems.
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Theil-Based Countermeasure against Interest Flooding Attacks for Named Data Networks

TL;DR: A TC is proposed to detect the distributions of normal and malicious interest packets in the NDN routers to further identify the IFA and the results show the efficiency of the TC for mitigating the IFAs and its advantages over other typical IFA countermeasures.
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Sentiment Analysis via Deep Multichannel Neural Networks With Variational Information Bottleneck

TL;DR: A novel sentiment analysis model named MBGCV is designed to alleviate problems and improve the accuracy and the performance of text sentiment analysis, which employs a multichannel paradigm and integrates Bidirectional Gated Recurrent Unit, Convolutional Neural Network and Variational Information Bottleneck.