In the end of last year I got to present my paper at the IEEE BigData 2023.

This work was a continuation on my uncertainty and sustainability research for big data streams (mostly focused on Video streams).

I believe that more and more people are aware of the effects of many real-world uncertainties and the necessity of providing sustainable (less energy) solutions for this kind of big data applications. One could even say that… people are more certain on the effect of these uncertainties *pun intended* .

But really, just to give an very brief idea, we show in the paper that one can save almost up to 10% of a Cloud server energy consumption in one year, if one decides to take into account the effects of some uncertainties present in the application. For reference, that’s more than the electricity consumed by a Tesla car in a round-trip of 1000km (from Amsterdam to Paris, and back). You can check more about this, and some other reference numbers in the paper that I linked bellow.

I’m again, posting my accepted version to keep this copy for myself. Inside the PDF there is a link to the final published version on IEEE Xplore.:

Uncertainty-Aware Optimisation for Sustainable Multimedia Event Processing in Big Data Streams.