All Outputs (4)

Modeling and analysis of a deep learning pipeline for cloud based video analytics (2017)
Presentation / Conference Contribution
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 Techn

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. These systems necessitate massive amounts of labeled data and training time... Read More about Modeling and analysis of a deep learning pipeline for cloud based video analytics.

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 (153-17

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.