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Scheduling Policies in Edge Computing for Real-Time Video Analytics

Publication Type : Conference Paper

Publisher : IEEE

Source : 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)

Url : https://doi.org/10.1109/idciot64235.2025.10915127

Campus : Bengaluru

School : School of Computing

Department : Computer Science and Engineering

Year : 2025

Abstract : This study compares different scheduling algorithms used in edge computing for real-time video processing. Instead of sending video data to cloud servers, the video is processed directly at the edge, reducing delays and saving bandwidth. The focus is on how different scheduling methods manage resources, prioritize tasks, and reduce the time it takes to analyze video. The algorithms are tested in simulated environments to understand how they impact system efficiency and performance. The goal of this work is to find the best scheduling policies for real-time video processing at the edge, improving overall system performance and scalability.

Cite this Research Publication : Shreevatsan S S, Yasasree Lasya Annambhotla, Anaswara Reji, Shinu M Rajagopal, Scheduling Policies in Edge Computing for Real-Time Video Analytics, 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), IEEE, 2025, https://doi.org/10.1109/idciot64235.2025.10915127

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