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Ying Cai
Researcher at Beijing Information Science & Technology University
Publications - 11
Citations - 352
Ying Cai is an academic researcher from Beijing Information Science & Technology University. The author has contributed to research in topics: Information privacy & Mobile ad hoc network. The author has an hindex of 6, co-authored 10 publications receiving 251 citations.
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A Privacy-Preserving Scheme for Incentive-Based Demand Response in the Smart Grid
TL;DR: This paper proposes a privacy-preserving scheme for IDR programs in the smart grid, which enables the DR provider to compute individual demand curtailments and DR rewards while preserving customer privacy.
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Smart Cities on Wheels: A Newly Emerging Vehicular Cognitive Capability Harvesting Network for Data Transportation
TL;DR: Considering the abundant storage of on-board CR routers and a wide range of under-utilized spectrum, the V-CCHN is expected to effectively transport substantial amounts of data between end devices and data networks, which offers an effective solution to handling the explosive wireless data traffic.
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A Conditional Privacy Protection Scheme Based on Ring Signcryption for Vehicular Ad Hoc Networks
Ying Cai,Hao Zhang,Yuguang Fang +2 more
TL;DR: This work designs a novel conditional privacy protection scheme based on ring signcryption, which utilizes the salient features of identity-based cryptosystems and ring signature to achieve conditional privacy.
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Intelligent Data Transportation in Smart Cities: A Spectrum-Aware Approach
TL;DR: Through extensive simulations, it is demonstrated that, with the developed data transportation scheme, the V-CCHN is effective in offering data transportation services despite its dependence on dynamic resources, such as vehicles and harvested spectrum resources.
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An Energy-Efficient Strategy for Secondary Users in Cooperative Cognitive Radio Networks for Green Communications
TL;DR: This paper proposes an energy-efficient cooperative strategy by leveraging temporal and spatial diversity of the primary network and formulate this decision-making problem based on the optimal stopping theory to maximize SUs' energy efficiency.