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<p>We investigate the evolution of the reliability of a mobile communication network through its capacity to avoid and withstand faults (called <i>robustness</i>) and to maintain proper functioning if faults occur nevertheless (called <i>resilience</i>). Our case study focuses on a swarm of nanosatellites orbiting the Moon and operating as a distributed space interferometer. The objective of this study is to evaluate the impact of graph division techniques on the robustness and resilience of the system, simultaneously. A high reliability level is key to guaranteeing proper quality of service by recovering from impairments while preserving the primary function or mission of the mobile network. By analyzing the effects of exploration and random selection algorithms on the network reliability, our results show that fair graph division significantly improves robustness metrics such as routing cost and network efficiency, while introducing a measurable tradeoff with specific resilience metrics such as path redundancy and disparity. In addition, our analysis highlights the superior performance of sequential exploration algorithms, such as MIRW, in optimizing robustness while preserving a decent level of resilience.</p>

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Enhancing the Reliability of Swarming Ad-hoc Networks

  • 期刊论文

  • 发表日期：

    2026年7月25日

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  • Evelyne Akopyan,
  • Emmanuel Lochin,
  • Riadh Dhaou,
  • Bernard Pontet,
  • Jacques Sombrin

摘要

We investigate the evolution of the reliability of a mobile communication network through its capacity to avoid and withstand faults (called robustness) and to maintain proper functioning if faults occur nevertheless (called resilience). Our case study focuses on a swarm of nanosatellites orbiting the Moon and operating as a distributed space interferometer. The objective of this study is to evaluate the impact of graph division techniques on the robustness and resilience of the system, simultaneously. A high reliability level is key to guaranteeing proper quality of service by recovering from impairments while preserving the primary function or mission of the mobile network. By analyzing the effects of exploration and random selection algorithms on the network reliability, our results show that fair graph division significantly improves robustness metrics such as routing cost and network efficiency, while introducing a measurable tradeoff with specific resilience metrics such as path redundancy and disparity. In addition, our analysis highlights the superior performance of sequential exploration algorithms, such as MIRW, in optimizing robustness while preserving a decent level of resilience.