Titlebook: Wireless Algorithms, Systems, and Applications; 15th International C Dongxiao Yu,Falko Dressler,Jiguo Yu Conference proceedings 2020 Spring

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Motilin

Multi-user Cooperative Computation Offloading in Mobile Edge Computingdge. In a multi-user MEC system, the MEC server may not be able to process the tasks offloaded from all users in its coverage area since it has limited computation resources as compared to the remote cloud. Device-to-device (D2D) assisted computation offloading may help to relieve the pressure on th

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SDTCNs: A Symmetric Double Temporal Convolutional Network for Chinese NERaracter-based models and word-based models. Character-based models cannot effectively utilize the inherent information of a word. Word-based models cannot effectively disambiguate words under different word segmentation norms. In this paper, we propose a symmetric double temporal convolutional netwo

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Verifiable Encrypted Search with Forward Secure Updates for Blockchain-Based System advances in cloud computing are further pushing forward the development of this technique, known as searchable encryption. However, existing encrypted search schemes mainly consider a centralized setting, where a search is conducted in a traditional client-server model. How to apply searchable encr

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Conference proceedings 2020ns, WASA 2020, which was held during September 13-15, 2020. The conference was planned to take place in Qingdao, China; due to the COVID-19 pandemic it was held virtually.?.The 67 full and 14 short papers presented in these proceedings were carefully reviewed and selected from 216 submissions. These

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A Novel Blockchain Network Structure Based on Logical Nodes nodes is similar. The experimental simulation results show that the proposed new blockchain network structure can effectively reduce the storage usage of physical nodes and decrease the difficulty to deploy blockchain to the edge network.

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Learning-Aided Mobile Charging for Rechargeable Sensor Networksvel cost assignment. By leveraging a . (MAB) framework, we propose a learning-aided mobile charger scheduling algorithm, namely “BanditCharger”, which induces a regret growing logarithmically with respect to the number of the sequential cycles. The efficacy of BanditCharger also can be verified by extensive simulations

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