How Can Researchers Evaluate Their New Thoughts for ISTNs?

3.1 ENE Requirements

Ideally, an ENE built for ISTN research is expected to simultaneously accomplish acceptable realism and flexibility. We summarize four baseline requirements as follows.

• (1) Constellation-consistency. The ENE is expected to be spatially and temporally consistent to the characteristics of real mega-constellations. For example, the ENE is desired to mimic a large number of network nodes at the same scale of a real mega-constellation, and can characterize the high dynamicity of LEO satellites, as well as its impact on network conditions (e.g., connectivity, delay variations).

• (2) System-level and networking stack realism. The ENE is expected to run user-defined system codes and network functionalities like in a real system and networking stack.

• (3) Flexible and scalable environment. Emerging megaconstellations are evolving rapidly. As most state-of-the-art constellations are still not in their final stage, the ENE is expected to flexibly support various network topologies at different scales to meet diverse research requirements.

• (4) Open, low-cost and easy-to-use interface. Finally, it is expected that the ENE could be open to the community, and can provide low-cost and easy-to-use programmable interfaces for researchers to carry out various experiments.

3.1 实验性网络环境（ENE）的核心要求

为实现天地一体化网络（ISTN）研究，理想的实验性网络环境需同时满足 高仿真度 与 高灵活性 双重目标。我们提炼出四项基础性要求：

（1）星座一致性：实验环境需在空间与时间维度上保持与真实巨型星座系统特性的一致性。

例如，ENE应能模拟与真实巨型星座规模相当的节点数量，并准确表征LEO卫星的高动态性特征及其对网络状态（如连通性、时延波动）的影响。

（2）系统级与协议栈真实性：ENE需具备运行用户自定义系统代码与网络功能的能力，其行为特征应与真实系统及网络协议栈保持一致。

（3）灵活可扩展架构：当前巨型星座系统仍处于快速演进阶段，多数前沿系统尚未定型。

因此，ENE需灵活支持不同规模的多样化网络拓扑结构，以满足异构研究需求。

（4）开放低门槛接口：实验环境应向学界开放并提供低成本、易用性强的可编程接口，使研究人员能够便捷开展各类实验验证。

3.2 Why Existing ENEs are Insufficient

Existing approaches for building an ENE can be classified into three categories, differing in their realism, flexibility and cost: (1)live LSNs/platforms, (2)simulators, and (3)emulators.

3.2 现有实验性网络环境（ENE）的局限性分析

现有构建实验性网络环境的方法可分为三类，其在真实性、灵活性与成本方面存在显著差异：（1）真实LSN或平台；（2）模拟器；（3）仿真器。

Live LSNs or platforms. A straightforward approach for ISTN experimentation is to construct an ENE based on live LSNs, e.g., recently SpaceX’s Starlink has started its initial services in certain regions. Although this approach guarantees good realism, directly manipulating and inspecting a live LSN might be technically and economically difficult for a common research group. Current live LSNs are also limited in their flexibility when they face diverse, exploratory research requirements. Realistic mega-constellations are still under-constructed and evolving rapidly, and their regulatory information in practice cannot be flexibly modified for what-if analysis. Further, the network community has many public experimentation platforms [7,20] that can be shared among researchers. However, these platforms are originally designed for tests in terrestrial networks, not for ISTNs, and thus cannot characterize the unique network behaviors under large-scale LEO dynamics.

真实LSN或实验平台

基于真实LSN构建ENE（如SpaceX星链系统已在部分地区开展试运营）虽能保证高仿真度，但对于普通研究机构而言，直接操控与监测真实卫星网络面临技术与经济双重障碍[4,8]。现有真实LSN在应对多样化探索性研究需求时灵活性受限：巨型星座系统仍处于建设演化阶段，其实际运行参数无法灵活调整以支持假设性分析[34,36]。此外，尽管学界存在众多网络实验共享平台（如GENI、FABRIC等），但其设计目标面向地面网络，无法表征大规模LEO动态下的独特网络行为。

Note

真实的LSN实验平台肯定是最好的，但是问题在于：

1. 太贵
2. 完全源于实际，无法供科研“假设分析”使用

Simulators and orbit analysis tools for ISTNs. Numerical or discrete-event-based simulation presents another extreme as compared with live LSNs and platforms. STK [35] and GMAT [11] are representative orbit analysis tools that can perform complex analysis of spacecrafts as well as ground stations. However, both STK and GMAT mainly focus on orbit and spacecraft analysis and have limited support for network simulation. More recently, SNS3 [76], Hypatia [60] and StarPerf [61] are emerging simulators for ISTNs. SNS3 is an extension to the ns-3 platform, and it models a full satellite network with a geostationary (GEO) satellite and bent-pipe payload. Hypatia is a framework for simulating and visualizing the network behavior of emerging mega-constellations. Similarly, StarPerf is a simulator that enables users to characterize, estimate and understand the achievable network performance under a variety of constellation options. Although the above simulators can flexibly simulate various satellite characteristics as well as the impact of high dynamics on network behaviors, a fundamental limitation of those simulators is that they can not support the run of system codes/functionalities and interactive network traffic as in real deployments. The abstraction-level of simulators might be too high to capture system-level effects, and could hide other practical issues (e.g., software overhead under heavy workloads) in real systems.

ISTN模拟器与轨道分析工具

数值模拟与基于离散事件的仿真（如STK、GMAT等轨道分析工具）虽能实现复杂航天器-地面站分析，但对网络协议栈的支持有限。新兴ISTN模拟器（如SNS3、Hypatia、StarPerf）虽可灵活模拟卫星动态特性及其对网络行为的影响，但存在根本性缺陷：无法运行真实系统代码/功能，亦无法承载交互式网络流量。

模拟器的高抽象层级可能掩盖系统级效应（如高负载下的软件开销），导致与真实部署环境存在偏差。

Note

基于ns-3的离散事件网络模拟器肯定是很好的，比如 IMC20 的 Hypatia / SNS3 / StarPerf

但是问题在于:

1. 纯模拟，与现实数据毫无关系
2. 无法承载交互式网络流量
3. 高抽象层级 可能 掩盖系统级效应 (比如, 高负载下的软件开销)

Network emulators, and their variations. Emulation is a hybrid approach that integrates real applications, protocols and operating systems in a synthetic network environment. Similar to live networks, emulators can load and run real codes with interactive network traffic. Similar to simulators, emulators can support controllable and diverse topologies and their virtual hardware requires fewer resources as compared with live networks. The community has many prior efforts focusing on emulated environments, e.g., VM- or container-based emulation [6,45,54,55,68–70,72,79–81,84,85].

However, existing emulators suffer from two limitations when they are applied for generating ENEs for ISTN research.

First, they are not constellation-consistent, since existing emulators inherently lack the ability of mimicking planet-wide LEO dynamics and time-varying network behaviors in ISTNs.

Second, the network scale for mega-constellations could be significantly larger than that in prior experimentation. For example, authors in [54] use 10 physical machines (25 VMs on each) to support a networked cluster with 250 nodes. Etalon [69] is a container-based emulator and its local testbed uses four servers to emulate 48 hosts in a data center network.

Different from prior scenarios, ISTN experiments require a much larger network environment: only the first shell of Starlink Phase-I includes about 1584 LEO satellites. Since both VMs and containers can involve software overhead on the physical host machine, it is difficult for existing emulators (e.g., [54, 55, 68]) to support such large-scale and dynamic emulations for mega-constellations.

网络仿真器及其变体

仿真技术通过合成网络环境集成真实应用、协议与操作系统，兼具真实网络代码执行能力与模拟器拓扑灵活性。现有基于虚拟机/容器的仿真框架（如）虽在传统场景表现良好，但应用于ISTN研究时面临双重挑战：

1. 星座一致性缺失：缺乏对全球尺度LEO动态及时变网络行为的建模能力；
2. 规模可扩展性不足：巨型星座节点规模远超既有仿真框架容量（例如仅星链一期首层含1584颗LEO卫星），而虚拟机/容器的软件开销限制物理主机对超大规模动态仿真的支持。

Note

网络仿真器(mininet)，跟网络模拟器(ns-3)完全不一样啊！

现有的网络模拟器直接迁移到ISTN至少存在下面两个问题:

1. 无法做到星座一致性: 陆地观测并建模，达不到对全球尺度LEO动态的及时响应
2. 规模可扩展性不足: 巨型星座节点规模 远超 既有仿真框架容量，系统开销过大，很难实现

Our motivation. Table 1 summarizes the landscape of existing experimentation approaches that can be used to build ENEs. Collectively, we find that none of existing approaches can simultaneously satisfy the four expected features. Limitations of existing approaches thus motivate us to seek for a constellation-consistent, credible, flexible, and low-cost methodology to advance the test and evaluation of new research for futuristic ISTNs. We present such a framework, namely STARRY NET, aiming at empowering researchers to build ENEs accomplishing the four goals as described in §3.1.

研究动机

如表1所示，现有实验方法均无法同时满足§3.1所述的四项核心需求。这一局限性促使我们探索 星座一致性强、可信度高、灵活可扩展且低成本 的新方法，以支持未来ISTN创新研究的测试评估。

基于此，本文提出STARRY NET框架，致力于赋能研究者构建符合§3.1目标的新型实验性网络环境。