All Outputs (43)

Application of immersive virtual reality mirror therapy for upper limb rehabilitation after stroke: a scoping review (2024)
Journal Article
Gebreheat, G., Antonopoulos, N., & Porter-Armstrong, A. (2024). Application of immersive virtual reality mirror therapy for upper limb rehabilitation after stroke: a scoping review. Neurological Sciences, 45(9), 4173-4184. https://doi.org/10.1007/s10072-024-07543-3

Mirror therapy is a commonly used rehabilitation intervention in post stroke upper limb rehabilitation. Despite many potential technological developments, mirror therapy is routinely delivered through the use of a static mirror or mirror box. This re... Read More about Application of immersive virtual reality mirror therapy for upper limb rehabilitation after stroke: a scoping review.

Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage (2024)
Journal Article
Davies-Tagg, D., Anjum, A., Zahir, A., Liu, L., Yaseen, M. U., & Antonopoulos, N. (2024). Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage. Big Data Mining and Analytics, 7(2), 371-398. https://doi.org/10.26599/bdma.2023.9020039

Data temperature is a response to the ever-growing amount of data. These data have to be stored, but they have been observed that only a small portion of the data are accessed more frequently at any one time. This leads to the concept of hot and cold... Read More about Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage.

A Survey on Event Tracking in Social Media Data Streams (2023)
Journal Article
Han, Z., Shi, L., Liu, L., Jiang, L., Fang, J., Lin, F., Zhang, J., Panneerselvam, J., & Antonopoulos, N. (2024). A Survey on Event Tracking in Social Media Data Streams. Big Data Mining and Analytics, 7(1), 217-243. https://doi.org/10.26599/bdma.2023.9020021

Social networks are inevitable parts of our daily life, where an unprecedented amount of complex data corresponding to a diverse range of applications are generated. As such, it is imperative to conduct research on social events and patterns from the... Read More about A Survey on Event Tracking in Social Media Data Streams.

Optimal controller selection and migration in large scale software defined networks for next generation internet of things (2023)
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 revolutionize the conventional approach, aiming to overcome the limitations o... Read More about Optimal controller selection and migration in large scale software defined networks for next generation internet of things.

A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics (2021)
Journal Article
Ali, H., Tariq, U. U., Hardy, J., Zhai, X., Lu, L., Zheng, Y., Bensaali, F., Amira, A., Fatema, K., & Antonopoulos, N. (2021). A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics. Computer Science Review, 41, Article 100416. 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 Nodes (SNs) to the Internet. Due to their high performance and exceptional... Read More about A survey on system level energy optimisation for MPSoCs in IoT and consumer electronics.

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.

Cloud-based video analytics using convolutional neural networks (2018)
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 analytics systems work on shallow networks and are unable to harness the power of... Read More about Cloud-based video analytics using convolutional neural networks.

Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds (2018)
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 supporting classification is developed on these video streams using cloud-based infr... Read More about Deep Learning Hyper-Parameter Optimization for Video Analytics in Clouds.

An approach to optimise resource provision with energy-awareness in datacentres by combating task heterogeneity. (2018)
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 during their actual execution. This inherent task heterogeneity imposes incre... Read More about An approach to optimise resource provision with energy-awareness in datacentres by combating task heterogeneity..

An investigation into the impacts of task-level behavioural heterogeneity upon energy efficiency in Cloud datacentres (2018)
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 tasks, such tasks usually exhibit increased level of behavioural heterogeneity... Read More about An investigation into the impacts of task-level behavioural heterogeneity upon energy efficiency in Cloud datacentres.

Big data analytics in healthcare: A cloud based framework for generating insights (2017)
Book Chapter
Anjum, A., Aizad, S., Arshad, B., Subhani, M. M., Davies-Tagg, D., Abdullah, T., & Antonopoulos, N. (2017). Big data analytics in healthcare: A cloud based framework for generating insights. In N. Antonopoulos, & L. Gillam (Eds.), Cloud Computing (153-170). Springer. https://doi.org/10.1007/978-3-319-54645-2_6

With exabytes of data being generated from genome sequencing, a whole new science behind genomics big data has emerged. As technology improves, the cost of sequencing a human genome has gone down considerably increasing the number of genomes being se... Read More about Big data analytics in healthcare: A cloud based framework for generating insights.

InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments (2017)
Journal Article
Panneerselvam, J., Liu, L., & Antonopoulos, N. (2018). InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments. Future Generation Computer Systems, 80, 322-341. https://doi.org/10.1016/j.future.2017.05.022

Cloud Computing has emerged as a low cost anywhere anytime computing paradigm. Given the energy consumption characteristics of the Cloud resources, service providers are under immense pressure to reduce the energy implications of the datacentres. For... Read More about InOt-RePCoN: Forecasting user behavioural trend in large-scale cloud environments.

Efficient service discovery in decentralized online social networks (2017)
Journal Article
Yuan, B., Liu, L., & Antonopoulos, N. (2018). Efficient service discovery in decentralized online social networks. Future Generation Computer Systems, 86, 775-791. https://doi.org/10.1016/j.future.2017.04.022

Online social networks (OSN) have attracted millions of users worldwide over the last decade. There are a series of urgent issues faced by existing OSN such as information overload, single-point of failure and privacy concerns. The booming Internet o... Read More about Efficient service discovery in decentralized online social networks.

Mobilouds: An Energy Efficient MCC Collaborative Framework With Extended Mobile Participation for Next Generation Networks (2016)
Journal Article
Panneerselvam, J., Hardy, J., Liu, L., Yuan, B., & Antonopoulos, N. (2016). Mobilouds: An Energy Efficient MCC Collaborative Framework With Extended Mobile Participation for Next Generation Networks. IEEE Access, 4, 9129-9144. https://doi.org/10.1109/access.2016.2602321

Given the emergence of mobile cloud computing (MCC), its associated energy implications are witnessed at larger scale. With offloading computationally intensive tasks to the cloud datacentres being the basic concept behind MCC, most of the mobile ter... Read More about Mobilouds: An Energy Efficient MCC Collaborative Framework With Extended Mobile Participation for Next Generation Networks.

An efficient algorithm for partially matched services in internet of services (2016)
Journal Article
Ahmed, M., Liu, L., Hardy, J., Yuan, B., & Antonopoulos, N. (2016). An efficient algorithm for partially matched services in internet of services. Personal and Ubiquitous Computing, 20(3), 283-293. https://doi.org/10.1007/s00779-016-0917-9

Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This large-scale information exchange res... Read More about An efficient algorithm for partially matched services in internet of services.

A socioecological model for advanced service discovery in machine-to-machine communication networks (2016)
Journal Article
Liu, L., Antonopoulos, N., Zheng, M., Zhan, Y., & Ding, Z. (2016). A socioecological model for advanced service discovery in machine-to-machine communication networks. ACM transactions on embedded computing systems, 15(2), Article 38. https://doi.org/10.1145/2811264

The new development of embedded systems has the potential to revolutionize our lives and will have a significant impact on future Internet of Thing (IoT) systems if required services can be automatically discovered and accessed at runtime in Machine-... Read More about A socioecological model for advanced service discovery in machine-to-machine communication networks.

Video stream analysis in clouds: An object detection and classification framework for high performance video analytics (2016)
Journal Article
Tariq, M., Anjum, A., Abdullah, T., Tariq, M. F., Baltaci, Y., & Antonopoulos, N. (2016). Video stream analysis in clouds: An object detection and classification framework for high performance video analytics. IEEE Transactions on Cloud Computing, https://doi.org/10.1109/TCC.2016.2517653

Object detection and classification are the basic tasks in video analytics and become the starting point for other complex applications. Traditional video analytics approaches are manual and time consuming. These are subjective due to the very involv... Read More about Video stream analysis in clouds: An object detection and classification framework for high performance video analytics.

A critical review of the routing protocols in opportunistic networks. (2014)
Journal Article
Panneerselvam, J., Atojoko, A., Smith, K., Liu, L., & Antonopoulos, N. (2014). A critical review of the routing protocols in opportunistic networks. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 1(1), Article e6. https://doi.org/10.4108/inis.1.1.e6

The goal of Opportunistic Networks (OppNets) is to enable message transmission in an infrastructure less environment where a reliable end-to-end connection between the hosts in not possible at all times. The role of OppNets is very crucial in today’s... Read More about A critical review of the routing protocols in opportunistic networks..