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Parallel and Distributed Processing in the Context of Fog Computing: High Throughput Pattern Matching and Distributed Monitoring

, 2018
Charalampos Stylianopoulos
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cuteSV-OL: a real-time structural variation detection framework for nanopore sequencing devices. [PDF]

Bioinformatics
Guo W, Liu Y, Wang Y, Jiang T.
europepmc   +1 more source

Design of multi-mode intelligent system architecture for surface defect detection of steel based on cloud technology. [PDF]

Sci Rep
Ren F, Xu L, Fei J, Tomas JPQ, Li H, Doma BT.   +5 more
europepmc   +1 more source

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In‐Sensor Computing: Materials, Devices, and Integration Technologies

Advances in Materials, 2022
The number of sensor nodes in the Internet of Things is growing rapidly, leading to a large volume of data generated at sensory terminals. Frequent data transfer between the sensors and computing units causes severe limitations on the system performance ...
Tianqing Wan, Bangjie Shao, Sijie Ma, Yue-Han Zhou, Qiao Li, Yang Chai   +5 more
semanticscholar   +1 more source

Space/Aerial-Assisted Computing Offloading for IoT Applications: A Learning-Based Approach

IEEE Journal on Selected Areas in Communications, 2019
Internet of Things (IoT) computing offloading is a challenging issue, especially in remote areas where common edge/cloud infrastructure is unavailable.
Nan Cheng, Feng Lyu, Wei Quan, Conghao Zhou, Hongli He, Weisen Shi, X. Shen   +6 more
semanticscholar   +1 more source

MXene‐ZnO Memristor for Multimodal In‐Sensor Computing

Advanced Functional Materials, 2021
Recently, in‐sensor computing with individual sensors or multiple connected sensors directly processing information has been proposed to improve energy, area, and time efficiency of artificial intelligence systems.
Yan Wang, Yue Gong, Lin Yang, Ziyu Xiong, Ziyu Lv, Xuechao Xing, Ye Zhou, Bing Zhang, C. Su, Qiufan Liao, Su‐Ting Han   +10 more
semanticscholar   +1 more source

Edge Computing for Autonomous Driving: Opportunities and Challenges

Proceedings of the IEEE, 2019
Safety is the most important requirement for autonomous vehicles; hence, the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety ...
Shaoshan Liu, Liangkai Liu, Jie Tang, Bo Yu, Yifan Wang, Weisong Shi   +5 more
semanticscholar   +1 more source

Blockchain-Based On-Demand Computing Resource Trading in IoV-Assisted Smart City

IEEE Transactions on Emerging Topics in Computing, 2021
In a smart city, Mobile Edge Computing (MEC) are generally deployed in static fashion in base stations (BSs). While moving vehicles with advanced on-board equipment can be regarded as dynamic computing resource transporters ignoring geographical ...
Xi Lin, Jun Wu, Shahid Mumtaz, S. Garg, Jianhua Li, M. Guizani   +5 more
semanticscholar   +1 more source

What Is Cloud Computing?

Cloud Technologies, 2019
Cloud computing is a distributed environment for multiple organizations to use remotely and get high scalability, reliability on anytime, anywhere, and pay-as-you-go concepts.
Ekaba Bisong
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Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks

IEEE Transactions on Vehicular Technology, 2019
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to the edge of Internet of Things (IoT) system. However, the static edge server deployment may cause “service hole” in IoT networks in which the location and service ...
Yi Liu, Huimin Yu, Shengli Xie, Yan Zhang   +3 more
semanticscholar   +1 more source