Enhancing Rendering Performance in Complex Visualizations by using Optimization Techniques and Algorithms in Browser Environments

Authors

  • Sanja Brekalo Medimurje University of Applied Sciences in Cakovec, Croatia
  • Klaudio Pap Faculty of Graphic Arts, University of Zagreb, Croatia
  • Bruno Trstenjak Međimurje University of Applied Sciences in Čakovec
Volume: 14 | Issue: 3 | Pages: 14049-14055 | June 2024 | https://doi.org/10.48084/etasr.7201

Abstract

This research is based on the hypothesis that optimization techniques can significantly improve the performance of complex visualizations in web browsers. The aim of the former was to determine to which extent the optimization can be achieved. Optimizations were coded to improve visualization, reduce the need for visual rendering, and decrease script execution time as well as the needed resources. To test the hypothesis, various optimization methods and algorithms were implemented on the initial visualization script and were tested. The main goal of this implementation was to assess how optimization methods, including quadtrees, spatial hashing, binning, LOD adjustments, and the use of the map data structure, affect the performance of web visualization. The obtained results confirmed the hypothesis and the original animation was significantly improved. The implementation of optimizations had a positive effect on the performance of visualizations. The conducted tests gave concrete evidence confirming the validity of the initial hypothesis. This led to certain conclusions regarding which methods provide the best results when optimizing complex visualizations. Key recommendations for code optimization, which can be used in the development of complex visualizations in web browsers, were derived.

Keywords:

optimization, complex visualizations, browser environments, spatial indexing algorithms, performance enhancement

Downloads

Download data is not yet available.

References

R. V. V. Krishna and S. Srinivas Kumar, "Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation," Engineering, Technology & Applied Science Research, vol. 6, no. 5, pp. 1182-1186, Oct. 2016.

B. K. Alsaidi, B. J. Al-Khafaji, and S. A. A. Wahab, "Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm," Engineering, Technology & Applied Science Research, vol. 9, no. 2, pp. 3892-3895, Apr. 2019.

S. Alkhliwi, "Huffman Encoding with White Tailed Eagle Algorithm-based Image Steganography Technique," Engineering, Technology & Applied Science Research, vol. 13, no. 2, pp. 10453-10459, 2023.

M. Platings and A. M. Day, "Compression of large-scale terrain data for real-time visualization using a tiled quad tree," Computer Graphics Forum, vol. 23, no. 4, pp. 741-759, Dec. 2004.

W. Duan, J. Luo, G. Ni, B. Tang, Q. Hu, and Y. Gao, "Exclusive grouped spatial hashing," Computers & Graphics, vol. 70, pp. 71–79, Feb. 2018.

M. Trapp and J. Döllner, "Interactive Close-Up Rendering for Detail+Overview Visualization of 3D Digital Terrain Models," in 2019 23rd International Conference Information Visualisation (IV), Paris, France, Jul. 2019, pp. 275–280.

S. Weiss and R. Westermann, "Differentiable Direct Volume Rendering," IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 1, pp. 562-572, Jan. 2022.

Q. Zaheer and J. Masud, "Visualization of flow field of a liquid ejector pump using embedded LES methodology," Journal of Visualization, vol. 20, no. 4, pp. 777-788, Nov. 2017.

M. Auer and A. Zipf, "3D WebGIS: From Visualization to Analysis. An Efficient Browser-Based 3D Line-of-Sight Analysis," ISPRS International Journal of Geo-Information, vol. 7, no. 7, Jul. 2018, Art. no. 279.

M. Emelianenko, "Fast Multilevel CVT-Based Adaptive Data Visualization Algorithm," Numerical Mathematics-Theory Methods and Applications, vol. 3, no. 2, pp. 195-211, May 2010.

B. Subbaraman, S. Shim, and N. Peek, "Forking a Sketch: How the OpenProcessing Community Uses Remixing to Collect, Annotate, Tune, and Extend Creative Code," in Proceedings of the 2023 ACM Designing Interactive Systems Conference, New York, NY, USA, Apr. 2023, pp. 326–342.

C. Orban, C. D. Porter, N. K. Brecht, R. M. Teeling-Smith, and K. A. Harper, "A novel approach for using programming exercises in electromagnetism coursework," in 2017 Physics Education Research Conference Proceedings, Mar. 2018, pp. 288–291.

C. Gasch, M. Chover, I. Remolar, and C. Rebollo, "Procedural modelling of terrains with constraints," Multimedia Tools and Applications, vol. 79, no. 41-42, pp. 31125-31146, Aug. 2020.

W. Lefer, B. Jobard, and C. Leduc, "High-quality animation of 2D steady vector fields," IEEE Transactions on Visualization and Computer Graphics, vol. 10, no. 1, pp. 2-14, Jan.-Feb. 2004.

"Binning in Data Mining," GeeksforGeeks. https://www.geeksforgeeks.org/binning-in-data-mining/.

"Spatial Hashing," GameDev.net. https://gamedev.net/tutorials/programming/general-and-gameplay-programming/spatial-hashing-r2697.

"Quad Tree," GeeksforGeeks. https://www.geeksforgeeks.org/quad-tree/.

"Optimizing p5.js Code for Performance," GitHub. https://github.com/processing/p5.js/wiki/Optimizing-p5.js-Code-for-Performance.

"Overview. A short introduction to the Processing software and projects from the community," Processing. https://processing.org//overview/.

"Home," p5.js. https://p5js.org/.

Downloads

How to Cite

[1]
Brekalo, S., Pap, K. and Trstenjak, B. 2024. Enhancing Rendering Performance in Complex Visualizations by using Optimization Techniques and Algorithms in Browser Environments. Engineering, Technology & Applied Science Research. 14, 3 (Jun. 2024), 14049–14055. DOI:https://doi.org/10.48084/etasr.7201.

Metrics

Abstract Views: 210
PDF Downloads: 311

Metrics Information