Pekka Pääkkönen

20022018
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Research Output 2002 2018

  • 5 Article
  • 3 Conference article in proceedings
  • 1 Published report
  • 1 Thesis

Architecture for Predicting Live Video Transcoding Performance on Docker Containers

Pääkkönen, P., Heikkinen, A. & Aihkisalo, T., 1 Jul 2018, 2018 IEEE International Conference on Services Computing, SCC 2018: Part of the 2018 IEEE World Congress on Services. Institute of Electrical and Electronic Engineers IEEE, p. 65-72 8 p. 8456402

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsResearchpeer-review

Program processors
Containers
Bandwidth
Costs
Virtual machine

Fast and easy live video service setup using lightweight virtualization

Heikkinen, A., Pääkkönen, P., Viitanen, M., Vanne, J., Riikonen, T. & Bakanoglu, K., 12 Jun 2018, Proceedings of the 9th ACM Multimedia Systems Conference, MMSys 2018. Association for Computing Machinery ACM, p. 487-489 3 p.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsResearchpeer-review

Demonstrations
Set-top boxes
Antenna feeders
Video cameras
Image coding
1 Citations

Quality management architecture for social media data

Pääkkönen, P. & Jokitulppo, J., 2017, In : Journal of Big Data. 4, 6, 26 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Quality management
Information management
Pipelines
Processing
Industry
4 Citations

Feasibility analysis of AsterixDB and Spark streaming with Cassandra for stream-based processing

Pääkkönen, P., 2016, In : Journal of Big Data. 3, 6, 25 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Electric sparks
Processing
Cloud computing
Information management
Throughput
19 Citations

Evaluating the quality of social media data in big data architecture

Immonen, A., Pääkkönen, P. & Ovaska, E., 2015, In : IEEE Access. 3, p. 2028-2043

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Industry
Decision making
Customer satisfaction
Pipelines
Big data