Sena Seneviratne

Affiliations:
  • Sydney University, School of Electrical & Information Engineering, Sydney Australia


According to our database1, Sena Seneviratne authored at least 11 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
Use of Computer Vision to Authenticate Retail Invoices with the Convolution-Neural Networks.
Proceedings of the Computer Science and Education. Computer Science and Technology, 2023

2021
Taxonomy And Survey Of Performance Prediction Systems For The Distributed Systems Including The Clouds.
Proceedings of the 2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, 2021

Design Of A Performance Prediction System For A Distributed Computer Environment And Its Adaptation On The Cloud Computing.
Proceedings of the 16th International Conference on Computer Science & Education, 2021

2020
Introduction of the new Operating System Kernel Internals for the New Metrics for the Performance Prediction on the Clouds.
Proceedings of the 15th International Conference on Computer Science & Education, 2020

2019
Computer Assisted Language Learning for Syllable-time Language Exposed Adults who are Learning a new Stress-Time Language.
Proceedings of the 14th International Conference on Computer Science & Education, 2019

2013
A Taxonomy of Performance Prediction Systems in the Parallel and Distributed Computing Grids.
CoRR, 2013

2011
Task profiling model for load profile prediction.
Future Gener. Comput. Syst., 2011

2010
Cost profile prediction for grid computing.
Concurr. Comput. Pract. Exp., 2010

2005
Host Load Prediction for Grid Computing Using Free Load Profiles.
Proceedings of the Distributed and Parallel Computing, 2005

Introduction to a New Tariff Mechanism for Charging for Computer Power in the Grid.
Proceedings of the Distributed and Parallel Computing, 2005

2004
Improving the Measurement of the Load Signal Through a More Appropriate Sampling Rate.
Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, 2004


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