All Outputs (3)

A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G (2019)
Journal Article
Lu, L., Liu, L., Panneerselvam, J., Yuan, B., Gu, J., & Antonopoulos, N. (2020). A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G. IEEE Transactions on Cognitive Communications and Networking, 6(2), 486-498. https://doi.org/10.1109/tccn.2019.2954388

The increasing deployments of 5G mobile communication system is expected to bring more processing power and storage supplements to Internet of Things (IoT) and mobile devices. It is foreseeable the billions of devices will be connected and it is extr... Read More about A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G.

Latency-Based Analytic Approach to Forecast Cloud Workload Trend for Sustainable Datacenters (2019)
Journal Article
Lu, Y., Liu, L., Panneerselvam, J., Zhai, X., Sun, X., & Antonopoulos, N. (2020). Latency-Based Analytic Approach to Forecast Cloud Workload Trend for Sustainable Datacenters. IEEE Transactions on Sustainable Computing, 5(3), 308-318. https://doi.org/10.1109/TSUSC.2019.2905728

Cloud datacenters are turning out to be massive energy consumers and environment polluters, which necessitate the need for promoting sustainable computing approaches for achieving environment-friendly datacentre execution. Direct causes of excess ene... Read More about Latency-Based Analytic Approach to Forecast Cloud Workload Trend for Sustainable Datacenters.

An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence (2019)
Journal Article
Yuan, B., Panneerselvam, J., Liu, L., Antonopoulos, N., & Lu, Y. (2019). An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence. IEEE Transactions on Industrial Informatics, 15(7), 4295-4305. https://doi.org/10.1109/tii.2019.2902877

Real-time data processing applications demand dynamic resource provisioning and efficient service discovery, which is particularly challenging in resource-constraint edge computing environments. Network embedding techniques can potentially aid effect... Read More about An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence.