BAROC: Concealing Packet Losses in LSNs with Bimodal Behavior Awareness for Livecast Ingestion

2025-04-22

AI Summary

To address burst packet loss, uplink bandwidth constraints, and failure of conventional recovery mechanisms caused by frequent satellite handovers in Low Earth Orbit Satellite Network (LSN) live streaming, this paper first identifies a bimodal distribution in network performance induced by satellite reassignment. Building upon this insight, we propose BAROC—a packet-loss concealment framework—and MTP-Informer, a novel temporal prediction model. Our approach jointly optimizes video encoding parameters and forward error correction (FEC) configurations, guided by bimodal behavior awareness and dynamic temporal modeling driven by MTP-Informer. Experimental results demonstrate that the proposed method achieves an average PSNR gain of 1.95 dB (up to 3.44 dB), significantly improves frame-rate stability, and enhances FEC packet utilization efficiency. Overall, it outperforms state-of-the-art video recovery solutions in LSN environments.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Learning to Search
• Computer Vision: Multi-modal Vision

Application Category

• Search and Retrieval-Augmented AI: Large language models for search
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

The advent of Low-Earth Orbit satellite networks (LSNs), exemplified by initiatives like emph{Starlink}, emph{OneWeb} and emph{Kuiper}, has ushered in a new era of ``Internet from Space"global connectivity. Recent studies have shown that LSNs are capable of providing unprecedented download capacity and low latency to support Livecast viewing. However, Livecast ingestion still faces significant challenges, such as limited uplink capacity, bandwidth degradation, and the burst of packet loss due to frequent satellite reallocations, which cause previous recovery and adaptive solutions to be inferior under this new scenario. In this paper, we conduct an in-depth measurement study dedicated to understanding the implications of satellite reallocations, which reveals that the network status during reallocations with network anomalies exhibits a different distribution, leading to bimodal behaviors on the overall network performance. Motivated by this finding, we propose BAROC, a framework that can effectively conceal burst packet losses by combining a novel proposed MTP-Informer with bimodal behavior awareness during satellite reallocation. BAROC enhances video QoE on the server side by addressing the above challenges and jointly determining the optimal video encoding and recovery parameters. Our extensive evaluation shows that BAROC outperforms other video delivery recovery approaches, achieving an average PSNR improvement of $1.95$ dB and a maximum of $3.44$ dB, along with enhancements in frame rate and parity packet utilization. Additionally, a comprehensive ablation study is conducted to assess the effectiveness of MTP-Informer and components in BAROC.

Problem

• Concealing burst packet losses in LSNs during satellite reallocations
• Addressing bimodal network behavior caused by satellite reallocations
• Optimizing video QoE via encoding and recovery parameter adjustments

Innovation

• BAROC conceals burst packet losses effectively
• Uses MTP-Informer with bimodal behavior awareness
• Optimizes video encoding and recovery parameters