K
Kai Lin
Researcher at Dalian University of Technology
Publications - 32
Citations - 942
Kai Lin is an academic researcher from Dalian University of Technology. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 10, co-authored 31 publications receiving 771 citations.
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Journal ArticleDOI
Enhanced Fingerprinting and Trajectory Prediction for IoT Localization in Smart Buildings
TL;DR: A novel localization approach that utilizes the neighbor relative received signal strength to build the fingerprint database and adopts a Markov-chain prediction model to assist positioning is proposed.
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VCMIA: A Novel Architecture for Integrating Vehicular Cyber-Physical Systems and Mobile Cloud Computing
TL;DR: A VCPS and MCC Integration Architecture (VCMIA) is designed, which provides mobile services for potential users such as drivers and passengers to access mobile traffic cloud and can provide the flexibility for enabling diverse applications.
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Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks
Hongjuan Li,Kai Lin,Keqiu Li +2 more
TL;DR: This paper proposes an energy-efficient and high-accuracy (EEHA) scheme for secure data aggregation that is more efficient and accurate than the existing scheme and conducts extensive simulations to evaluate the performance.
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Balancing energy consumption with mobile agents in wireless sensor networks
TL;DR: This paper demonstrates that for a sensor network with uniform node distribution and constant data reporting, balancing the energy of the whole network cannot be realized when the distribution of data among sensor nodes is unbalanced, and designs a method to mitigate the uneven energy dissipation problem by controlling the mobility of agents.
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Energy Efficiency QoS Assurance Routing in Wireless Multimedia Sensor Networks
TL;DR: A QoS trust estimation model based on social network analysis is designed, which enables each sensor node measuring the service quality by monitoring the behaviors of neighbor nodes, and shows the high performance of EEQAR routing in lifetime and quality of service.