Edinburgh Napier University

Optimal controller selection and migration in large scale software defined networks for next generation internet of things

Journal Article

Shahzad, M., Liu, L., Belkout, N., & Antonopoulos, N. (2023)

Optimal controller selection and migration in large scale software defined networks for next generation internet of things. SN Applied Sciences, 5(12), Article 309. https://doi.org/10.1007/s42452-023-05535-0

The substantial amount of IoT traffic, coupled with control messages, places a heavy burden on SDN controllers, which compromises their capacity. We investigate how SDN can re...

A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics

Journal Article

Ali, H., Tariq, U. U., Hardy, J., Zhai, X., Lu, L., Zheng, Y., …Antonopoulos, N. (2021)

A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics. Computer Science Review, 41, https://doi.org/10.1016/j.cosrev.2021.100416

Internet-of-Things (IoT) is an appealing service to revolutionise Smart City (SC) initiatives across the globe. IoT interconnects a plethora of digital devices known as Sensor...

A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G

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....

Latency-Based Analytic Approach to Forecast Cloud Workload Trend for Sustainable Datacenters

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 achie...

An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence

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 comp...

Cloud-based video analytics using convolutional neural networks

Journal Article

Yaseen, M. U., Anjum, A., Farid, M., & Antonopoulos, N. (2019)

Cloud-based video analytics using convolutional neural networks. Software: Practice and Experience, 49(4), 565-583. https://doi.org/10.1002/spe.2636

Object classification is a vital part of any video analytics system, which could aid in complex applications such as object monitoring and management. Traditional video analyt...

Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds

Journal Article

Yaseen, M. U., Anjum, A., Rana, O., & Antonopoulos, N. (2019)

Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds. IEEE Transactions on Systems Man and Cybernetics: Systems, 49(1), 253-264. https://doi.org/10.1109/TSMC.2018.2840341

A system to perform video analytics is proposed using a dynamically tuned convolutional network. Videos are fetched from cloud storage, preprocessed, and a model for supportin...

An approach to optimise resource provision with energy-awareness in datacentres by combating task heterogeneity.

Journal Article

Panneerselvam, J., Liu, L., & Antonopoulos, N. (2018)

An approach to optimise resource provision with energy-awareness in datacentres by combating task heterogeneity. IEEE Transactions on Emerging Topics in Computing, https://doi.org/10.1109/TETC.2018.2794328

Cloud workloads are increasingly heterogeneous such that a single Cloud job may encompass one to several tasks, and tasks belonging to the same job may behave distinctively du...

An investigation into the impacts of task-level behavioural heterogeneity upon energy efficiency in Cloud datacentres

Journal Article

Panneerselvam, J., Liu, L., Lu, Y., & Antonopoulos, N. (2018)

An investigation into the impacts of task-level behavioural heterogeneity upon energy efficiency in Cloud datacentres. Future Generation Computer Systems, 83, 239-249. https://doi.org/10.1016/j.future.2017.12.064

Cloud datacentre resources and the arriving jobs are addressed to be exhibiting increased level of heterogeneity. A single Cloud job may encompass one to several number of tas...

Modeling and analysis of a deep learning pipeline for cloud based video analytics

Conference Proceeding

Yaseen, M. U., Anjum, A., & Antonopoulos, N. (2017)

Modeling and analysis of a deep learning pipeline for cloud based video analytics. In BDCAT '17 Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, (121-130). https://doi.org/10.1145/3148055.3148081

Video analytics systems based on deep learning approaches are becoming the basis of many widespread applications including smart cities to aid people and traffic monitoring. T...