Deep-learning-enhanced multitarget detection for end–edge–cloud surveillance in smart IoT
Along with the rapid development of cloud computing, IoT, and AI technologies, cloud video
surveillance (CVS) has become a hotly discussed topic, especially when facing the …
surveillance (CVS) has become a hotly discussed topic, especially when facing the …
Deep-learning-enhanced human activity recognition for Internet of healthcare things
Along with the advancement of several emerging computing paradigms and technologies,
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …
Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning
L Wang, X Hu, Y Wang, S Xu, S Ma, K Yang, Z Liu… - Computer Networks, 2021 - Elsevier
Job-shop scheduling problem (JSP) is used to determine the processing order of the jobs
and is a typical scheduling problem in smart manufacturing. Considering the dynamics and …
and is a typical scheduling problem in smart manufacturing. Considering the dynamics and …
Federated transfer learning based cross-domain prediction for smart manufacturing
Smart manufacturing aims to support highly customizable production processes. Therefore,
the associated machine intelligence needs to be quickly adaptable to new products …
the associated machine intelligence needs to be quickly adaptable to new products …
Deep-reinforcement-learning-based mode selection and resource allocation for cellular V2X communications
Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
Cloud-native computing: A survey from the perspective of services
The development of cloud computing delivery models inspires the emergence of cloud-
native computing. Cloud-native computing, as the most influential development principle for …
native computing. Cloud-native computing, as the most influential development principle for …
Prediction-based scheduling techniques for cloud data center's workload: a systematic review
A cloud data center provides various facilities such as storage, data accessibility, and
running many specific applications on cloud resources. The unpredictable demand for …
running many specific applications on cloud resources. The unpredictable demand for …
Deep-reinforcement-learning-based QoS-aware secure routing for SDN-IoT
X Guo, H Lin, Z Li, M Peng - IEEE Internet of things journal, 2019 - ieeexplore.ieee.org
Recently, with the proliferation of communication devices, Internet of Things (IoT) has
become an emerging technology which facilitates massive devices to be enabled with …
become an emerging technology which facilitates massive devices to be enabled with …
esDNN: deep neural network based multivariate workload prediction in cloud computing environments
Cloud computing has been regarded as a successful paradigm for IT industry by providing
benefits for both service providers and customers. In spite of the advantages, cloud …
benefits for both service providers and customers. In spite of the advantages, cloud …
A quantum approach towards the adaptive prediction of cloud workloads
This work presents a novel Evolutionary Quantum Neural Network (EQNN) based workload
prediction model for Cloud datacenter. It exploits the computational efficiency of quantum …
prediction model for Cloud datacenter. It exploits the computational efficiency of quantum …