Ching-Hsien Hsu mainly investigates Cloud computing, Quality of service, Computer network, Server and Mobile device. Ching-Hsien Hsu interconnects Virtual machine, Recommender system, Distributed computing and Big data in the investigation of issues within Cloud computing. His research investigates the connection between Distributed computing and topics such as Real-time computing that intersect with problems in Greedy algorithm, Resource and Resource allocation.
His research integrates issues of Collaborative filtering, Data mining, Selection and Mobile QoS in his study of Quality of service. His studies in Computer network integrate themes in fields like Service quality and Cyber-physical system. Ching-Hsien Hsu has researched Mobile device in several fields, including Computer security, Enhanced Data Rates for GSM Evolution, Service, Smart city and Radio access network.
Distributed computing, Cloud computing, Computer network, Parallel computing and Scheduling are his primary areas of study. His research in Distributed computing intersects with topics in Grid computing, Data grid, Scalability and Server. His biological study spans a wide range of topics, including Virtual machine, Quality of service, Service and Big data.
His study in Quality of service is interdisciplinary in nature, drawing from both Web service, The Internet, Data mining and Mobile QoS. His study focuses on the intersection of Computer network and fields such as Mobile device with connections in the field of Computer security. His Scheduling research is multidisciplinary, incorporating perspectives in Symmetric multiprocessor system and Heterogeneous network.
His scientific interests lie mostly in Cloud computing, Artificial intelligence, Machine learning, Computer security and Distributed computing. His work carried out in the field of Cloud computing brings together such families of science as Workload, Smart city, Scheduling, Server and Mobile device. His Server study improves the overall literature in Computer network.
His work in the fields of Deep learning, Artificial neural network and Discriminative model overlaps with other areas such as Colorectal cancer and Clinical trial. Within one scientific family, he focuses on topics pertaining to Industrial Internet under Computer security, and may sometimes address concerns connected to Public-key cryptography. His studies link Edge computing with Distributed computing.
His primary scientific interests are in Cloud computing, Quality of service, Artificial intelligence, Workload and Mobile device. His Cloud computing study combines topics from a wide range of disciplines, such as Schedule and Service. He combines subjects such as Machine learning and Web service with his study of Quality of service.
His Artificial intelligence research integrates issues from Data science and Pattern recognition. His Workload study integrates concerns from other disciplines, such as Scheduling, Resource allocation and Operations research. The concepts of his Mobile device study are interwoven with issues in Computation and Smart city.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Biocloud: Cloud Computing for Biological, Genomics, and Drug Design
Ching-Hsien Hsu;Chun-Yuan Lin;Ming Ouyang;Yi Ke Guo.
BioMed Research International (2013)
Edge server placement in mobile edge computing
Shangguang Wang;Yali Zhao;Jinlinag Xu;Jie Yuan.
Journal of Parallel and Distributed Computing (2019)
Optimizing Energy Consumption with Task Consolidation in Clouds
Ching-Hsien Hsu;Kenn D. Slagter;Shih-Chang Chen;Yeh-Ching Chung.
Information Sciences (2014)
Machine Learning Based Big Data Processing Framework for Cancer Diagnosis Using Hidden Markov Model and GM Clustering
Gunasekaran Manogaran;V. Vijayakumar;R. Varatharajan;Priyan Malarvizhi Kumar.
Wireless Personal Communications (2018)
A Vertical Handoff Method via Self-Selection Decision Tree for Internet of Vehicles
Shangguang Wang;Cunqun Fan;Ching-Hsien Hsu;Qibo Sun.
IEEE Systems Journal (2016)
High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication
Jianqi Liu;Jiafu Wan;Dongyao Jia;Bi Zeng.
IEEE Communications Magazine (2017)
QoS prediction for service recommendations in mobile edge computing
Shangguang Wang;Yali Zhao;Lin Huang;Jinliang Xu.
Journal of Parallel and Distributed Computing (2017)
Provision of Data-Intensive Services Through Energy- and QoS-Aware Virtual Machine Placement in National Cloud Data Centers
Shangguang Wang;Ao Zhou;Ching-Hsien Hsu;Xuanyu Xiao.
IEEE Transactions on Emerging Topics in Computing (2016)
A Highly Accurate Prediction Algorithm for Unknown Web Service QoS Values
You Ma;Shangguang Wang;Patrick C.K. Hung;Ching-Hsien Hsu.
IEEE Transactions on Services Computing (2016)
Cold-Start Recommendation Using Bi-Clustering and Fusion for Large-Scale Social Recommender Systems
Daqiang Zhang;Ching-Hsien Hsu;Min Chen;Quan Chen.
IEEE Transactions on Emerging Topics in Computing (2014)
Profile was last updated on December 6th, 2021.
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