Y
Yan Sun
Researcher at Beijing University of Posts and Telecommunications
Publications - 89
Citations - 682
Yan Sun is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Routing protocol & Computer science. The author has an hindex of 12, co-authored 77 publications receiving 449 citations. Previous affiliations of Yan Sun include Queen Mary University of London.
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Energy Efficient Secure Computation Offloading in NOMA-Based mMTC Networks for IoT
TL;DR: This work forms the joint computation and communication resource allocation algorithm for secure computation offloading in NOMA-based mMTC networks for IoT, where the relay equipped with an MEC server and a passive malicious eavesdropper are presented.
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Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care.
Jose-Luis Bayo-Monton,Antonio Martinez-Millana,Weisi Han,Carlos Fernandez-Llatas,Carlos Fernandez-Llatas,Yan Sun,Vicente Traver,Vicente Traver +7 more
TL;DR: Evaluating a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi confirms that portable devices are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.
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A Decentralized Deadline-Driven Electric Vehicle Charging Recommendation
TL;DR: Evaluation results show the features of the MEC-based charging recommendation system in terms of communication efficiency (low cost for information dissemination and collection) and improvement of charging performance (reduced charging waiting time and increased fully charged EVs).
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Adaptive Cell Zooming and Sleeping for Green Heterogeneous Ultradense Networks
TL;DR: This paper researches on the adaptive cell zooming scheme to achieve the optimized user association through adjusting cell coverages and applies the game theory to optimize the CZF based on reduction of area power consumption.
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Cache-Aware Computation Offloading in IoT Systems
TL;DR: The computation offloading method with cached data is studied and an online offloading strategy is proposed, which approximates the global optimal solution and it reduces the weighted response time by about 26.13% on average compared to other competing algorithms.