Enhancing the Quantification of Capacity and Throughput in Integrated Space and Terrestrial Network

2024-11-23

arXiv.org

AI Summary

This paper addresses two critical issues in low-earth-orbit satellite networks (LSNs): the conflation of capacity and throughput, and the systematic overestimation of throughput by conventional flow models. It rigorously distinguishes infrastructure-inherent capacity—determined solely by inter-satellite link (ISL) topology and reliability—from scenario-dependent throughput, which is governed by routing policies and traffic load. To this end, it proposes cap-uISL, a capacity model independent of routing or congestion control, enabling quantitative calibration via ISL-level parameters. It further introduces THP-CPE, a throughput computation method based on constrained path expansion and empirically grounded traffic path sets, achieving path-aware, load-adaptive quantification. Evaluated across four emerging inter-satellite transport network (ISTN) architectures, THP-CPE yields significantly more accurate throughput estimates than traditional flow models, with markedly reduced estimation bias; path utilization remains consistently ≤1, ensuring physical feasibility and result credibility; and cap-uISL supports continuous, parameter-driven capacity adjustment—e.g., in response to uISL reliability variations.

Technology Category

• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Constraint Satisfaction and Optimization: Satisfiability
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Quantification of network capacity and throughput is crucial for performance evaluation of integrated space and terrestrial network (ISTN).However, existing studies mainly consider the maximum throughput as the network capacity, but such a definition would make it unreasonable that the value of the network capacity would change with different employed routing algorithms and congestion control policy, instead of being a constant quantity. In this paper, we argue that the capacity of an ISTN is solely dependent on the characteristics of the network infrastructure,and the throughput of an ISTN is the aggregate traffic transported by the network under a given traffic scenario. Then, we present a quantitative approach to assessing network capacity in relation to an unreliable ISL model (cap-uISL), and a Constrained Path Expansion throughput calculation method (THP-CPE) based on a set of known traffic paths. This method allows us to obtain the current throughput value of the network based on any given traffic paths and load demand matrix. As the traffic load increases, the throughput approaches its maximum value, which is notably smaller than the network's capacity. We experimentally determine the network capacity of CAP-uISL under various link parameters and compare our throughput quantization method, THP-CPE, with other state-of-the-art methods under four emerging ISTNs. We find that, compared with the THP-CPE, existing throughput calculation methods tend to be overestimated, while our proposed throughput calculation method maintains reasonable intervals in terms of path utilization ($<1$) under all load cases.

Problem

• Modeling time-varying capacity in unstable LEO satellite networks
• Correcting overestimation in flow-based throughput calculations
• Evaluating throughput under dynamic traffic and routing schemes

Innovation

• CAP-uLSN model characterizes time-varying capacity under unstable ISLs
• Monte Carlo framework probabilistically evaluates aggregate throughput performance
• Model provides guidance for optimizing routing and adaptive billing