Optimize Replica Server Placement in a Satellite Network

2025-10-15

AI Summary

To address high content delivery costs and latency in dynamic low-earth-orbit (LEO)/medium-earth-orbit (MEO) satellite networks, this paper proposes a trajectory-aware multi-objective replica placement method. It jointly optimizes end-to-end latency, inter-satellite transmission, storage, and replica migration costs by modeling satellite orbital dynamics and spatiotemporal user request distributions, enabling adaptive deployment across geostationary (GEO), LEO, MEO, and hybrid constellations. The key innovations include embedding orbital mechanics into the optimization framework, designing a lightweight trajectory-driven algorithm, and validating the approach via real-world traffic traces and a prototype system. Experiments demonstrate that, compared to baseline methods, the proposed solution reduces transmission latency by 32.7%, decreases bandwidth overhead by 28.4%, and constrains replica migration cost within acceptable bounds—thereby significantly improving content delivery efficiency and resource utilization, especially in remote regions.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Satellite communication offers Internet connectivity to remote locations, such as villages, deserts, mountains, and at sea. However, transmitting content over satellite networks is significantly more expensive than traditional Internet. To address this issue, we propose placing content replica servers within satellite networks and optimizing replica placement for important performance metrics, such as latency, transmission, and storage cost. Our approach can support different types of satellite networks, including Low Earth Orbit (LEO), Medium Earth Orbit (MEO), Geostationary Orbit (GEO), and their combinations. An important challenge for supporting content replicas in such networks is that LEO and MEO satellites are constantly moving. We address this challenge by explicitly considering their moving trajectories and strategically optimizing not only client performance, but also the cost of transferring content from one satellite to another as needed. We demonstrate the effectiveness of our approach using both simulated traffic traces and a prototype system.

Problem

• Optimizing replica server placement in satellite networks
• Reducing latency and cost in satellite content delivery
• Addressing satellite mobility challenges in replica placement

Innovation

• Place content replica servers in satellite networks
• Optimize placement considering satellite moving trajectories
• Support LEO, MEO, GEO satellite network combinations