H
Houbing Song
Researcher at Embry-Riddle Aeronautical University, Daytona Beach
Publications - 528
Citations - 17473
Houbing Song is an academic researcher from Embry-Riddle Aeronautical University, Daytona Beach. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 56, co-authored 425 publications receiving 11550 citations. Previous affiliations of Houbing Song include Shanxi Agricultural University & University of Virginia.
Papers
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Internet of Things and Big Data Analytics for Smart and Connected Communities
TL;DR: It is argued that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the Potential to enable the move from IoT to real-time control desired for S CC.
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ART: An Attack-Resistant Trust Management Scheme for Securing Vehicular Ad Hoc Networks
Wenjia Li,Houbing Song +1 more
TL;DR: An attack-resistant trust management scheme (ART) is proposed for VANets that is able to detect and cope with malicious attacks and also evaluate the trustworthiness of both data and mobile nodes in VANETs.
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Imperfect Information Dynamic Stackelberg Game Based Resource Allocation Using Hidden Markov for Cloud Computing
TL;DR: A cloud resource allocation model based on an imperfect information Stackelberg game (CSAM-IISG) using a hidden Markov model (HMM) in a cloud computing environment was shown to increase the profits of service providers and infrastructure suppliers simultaneously.
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A Scalable and Quick-Response Software Defined Vehicular Network Assisted by Mobile Edge Computing
TL;DR: An SDN-enabled network architecture assisted by MEC, which integrates different types of access technologies, is proposed, which can decrease data transmission time and enhance quality of user experience in latency-sensitive applications.
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Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics
TL;DR: Recent research in data types, storage models, privacy, data security, analysis methods, and applications related to network big data are reviewed.