A comprehensive analysis of power consumption and resources utilization in open-source and proprietary media players
Notice bibliographique
Résumé
The growing demand for high-quality media consumption has highlighted the importance of energy-efficient software, particularly media players that handle high-resolution video content. As public is concerned around environmental sustainability and energy use, evaluating the power consumption of software applications has become crucial. This thesis investigates the comparative energy efficiency of open-source and proprietary media players, with a focus on CPU, GPU, and memory consumption during high-resolution video playback. By analyzing resource usage across different platforms, this research aims to provide insights into how software architecture, codec support, and hardware acceleration affect the overall energy consumption of these media players. Open-source media players, such as VLC and MPV, are widely adopted due to their flexibility, cost-effectiveness, and support for a wide range of media formats. However, these players often rely heavily on CPU resources, particularly when hardware acceleration is not fully optimized. This can result in higher power consumption during high-demand tasks such as 4K video playback, especially on platforms where driver support for hardware acceleration is limited. Despite this, open-source players can be energy-efficient when optimized codecs like VP9 and AV1 are used, reducing file sizes and overall power consumption. Proprietary media players, including GOM Player and Windows Media Player, generally outperform their open-source counterparts in terms of energy use. These players benefit from close integration with hardware manufacturers, which allows for better utilization of hardware acceleration and more efficient resource management. Proprietary codecs such as H.264 and H.265 are optimized for energy savings by offloading video processing to the GPU, leading to lower CPU usage and reduced power consumption. The structured support and regular updates that come with proprietary software ensure that these players remain well-optimized for performance and energy efficiency over time. The study utilized real-time power consumption monitoring tools, including HWiNFO and PowerTOP, to assess the performance of both open-source and proprietary media players during high-definition video playback. Metrics such as CPU and GPU power consumption, memory usage, and overall system resource utilization were analyzed in various playback scenarios. The results indicate that proprietary media players typically consume less power due to optimized hardware and software integration, while open-source players can achieve competitive efficiency levels with appropriate codec and hardware configurations. In terms of long-term sustainability, proprietary players tend to offer more immediate energy savings, particularly in environments where media playback is frequent. However, open-source media players, with their flexibility and user-driven customization, present opportunities for power savings over time, especially in cost-sensitive environments. This thesis contributes to the understanding of software energy efficiency, providing valuable insights for developers and users aiming to optimize their media playback experience for reduced energy consumption and environmental impact.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».