Please wait ...
0% Complete
Home
/
15th International Conference on Computer and Knowledge Engineering
HV-RCE: Reducing Network Bandwidth Usage for Video Transmission via HEVC/VVC Features in Resource-Constrained Environments
Authors :
Yaghoub Saberi
1
Mohammadreza Forghani
2
Sharifeh Sadat Mirkhalaf
3
1- Department of Computer Engineering Na.C. , Islamic Azad University, Najafabad ,Iran.
2- Department of Computer Engineering Na.C. , Islamic Azad University, Najafabad ,Iran.
3- Department of Computer Engineering Na.C. , Islamic Azad University, Najafabad ,Iran.
Keywords :
Video Compression،HEVC/VVC،Adaptive Encoding،Bandwidth Optimization،Resource-Constrained Systems
Abstract :
The exponential growth of video data in modern communication systems has made efficient bandwidth usage a critical challenge, particularly in resource-constrained environments such as wireless sensor networks, vehicular ad hoc networks (VANETs), and remote monitoring systems. This paper introduces HV-RCE, a novel framework that reduces network bandwidth consumption for video transmission by leveraging advanced features of HEVC and VVC codecs. HV-RCE employs region-based complexity estimation, content-adaptive encoding, and bandwidth-aware optimization to dynamically adjust encoding parameters such as GOP structure, quantization levels, and coding tools based on real-time analysis of video content, device capabilities, and network conditions. Implemented on low-power platforms like the Raspberry Pi, the proposed method achieves a 35–45% reduction in average bitrate while maintaining or improving video quality (PSNR), lowering energy consumption, and reducing encoding latency compared to baseline approaches. With its modular and adaptive architecture, HV-RCE is well-suited for practical deployment in bandwidth- and resource-limited scenarios such as IoT-based surveillance, mobile edge computing, and smart vehicular systems.
Papers List
List of archived papers
A New Inter-layer Similarity metric for link prediction in multilayer networks
Alireza Abdollahpouri - Samira Rafiee
Farsi Text in Scene: A new dataset
Ali Salmasi - Ehsanollah Kabir
Capsule Routing over Stacked GCN-GAT Embeddings with Negative Sampling for Graph Link Prediction
Fatemeh Safari Sarvandi - Sayeh Mirzaei - Rooholah Abedian
Compressing Deep Neural Networks Using Explainable AI
Kimia Soroush - Mohsen Raji - Behnam Ghavami
HiCAP: Hierarchical Clustering-based Attention Pooling for Graph Representation Learning
Parsa Haddadian - Rooholah Abedian - Ali Moeini
Adaptive Pattern Reconstruction Using Linear Regression for Improved TPS Anomaly Detection
Ali Azarsina - Alireza Safarzadeh - MohammadReza Jamali - Abdolhossein Vahabie
Attention-Boosted Ensemble of Pre-trained Convolutional Neural Networks for Accurate Diabetic Retinopathy Detection
Benyamin Mirab Golkhatmi - Mohammad Hossein Moattar
Joint ADC-less Analog Demodulator and Decoder for Extended Binary (8, 4, 4) Hamming Channel Code
Mir Mahdi Safari - Jafar Pourrostam - Behzad Mozaffari Tazehkand
GroupRec: Group Recommendation by Numerical Characteristics of Groups in Telegram
Davod Karimpour - Mohammad Ali Zare Chahooki - Ali Hashemi
Optimizing Foreign Exchange Trading Performance Through Reinforcement Machine Learning Framework
Ervin Gubin Moung - Hani Yasmin Binti Murnizam - Maisarah Mohd Sufian - Valentino Liaw - Ali Farzamnia - Lorita Angeline
more
Samin Hamayesh - Version 44.8.0