Wild salmon are essential to the ecological, economic, and cultural sustainability of the North Pacific Rim. Yet climate variability, habitat loss, and data limitations in remote ecosystems that lack basic infrastructure support pose significant challenges to effective fisheries management. This project explores the integration of multimodal foundation AI and expert-in-the-loop frameworks to enhance wild salmon monitoring and sustainable fisheries management in Indigenous rivers across Pacific Northwest. By leveraging video and sonar-based monitoring, we develop AI-powered tools for automated species identification, counting, and length measurement, reducing manual effort, expediting delivery of results, and improving decision-making accuracy. Expert validation and active learning frameworks ensure ecological relevance while reducing annotation burdens. To address unique technical and societal challenges, we bring together a cross-domain, interdisciplinary team of university researchers, fisheries biologists, Indigenous stewardship practitioners, government agencies, and conservation organizations. Through these collaborations, our research fosters ethical AI co-development, open data sharing, and culturally informed fisheries management.

Inter-Satellite Links (ISLs) are pivotal for delivering global connectivity services and optimizing resource utilization in 6 G and beyond. However, delivering effective topology control services through ISL provisioning faces critical challenges insustainabilityandreliability. Reducing ISLs can conserve energy and extend satellite battery life for Low-Earth-Orbit (LEO) satellites where replacing batteries is impractical. Conversely, increasing ISLs can enhance service reliability but may lead to uneven traffic distribution, overloading nodes, and accelerating battery degradation, ultimately degrading the quality of 6 G services. To tackle this dilemma, we propose TASRI—a service-oriented framework forTraffic-Aware, Sustainable, and Reliable ISL provisioning. TASRI provides a dynamic topology control service by partitioning network topologies into logical zones, enabling flexible ISL activation and deactivation to adapt to varying service demands, ensuring efficient resource utilization and dynamic service orchestration. Using a sustainability-oriented weight model, we formulate the topology control service optimization problem and introduce a scalable on-demand topology evolving algorithm with a bounded approximation ratio. Extensive real-world deployment-based simulation results show that, compared to the state-of-the-art, our TASRI can substantially reduce battery life consumption, while achieving comparable reliability and excellent scalability with considerably fewer ISLs or ISL handovers.

Inter-Satellite Links (ISLs) are key for worldwide communication and efficient use of space networks in the future 6G network. However, they face challenges in sustainability and reliability. Reducing ISLs saves energy and extends battery life, which is critical since satellite batteries are hard to replace. More ISLs, however, can make the system more reliable but at the cost of higher energy use, especially problematic when traffic is uneven, speeding up battery wear. To tackle this dilemma, we for the first time develop a Traffic-Aware, Sustainable and Reliable ISL provisioning (TASRI) framework for LEO satellite constellation networks. In TASRI, ISLs can be flexibly switched on and off to better accommodate various traffic conditions as well as reliability and sustainability. We formulate the ISL provisioning problem based on the sustainability-oriented weight model and then propose an on-demand topology evolving algorithm. Extensive real-world deployment-based simulation results show that, compared to the state-of-the-art, our TASRI can substantially reduce battery life consumption, while achieving comparable reliability with considerably fewer ISLs.

Satellite networks are believed to become an indispensable component in the forthcoming 6G network and beyond. The surging demands attract numerous satellite network operators into this market to compete, yet also cooperate via resource sharing for cost and performance improvement, which is similar to the growth trajectory of how the Internet becomes the network of networks. Hence, we envision a federated network of satellite networks (shortened as federated satellite network) in this paper, where satellite network operators will eventually federate with each other to achieve a win-win situation. However, the yet-to-come federated satellite network faces two unique challenges: sustainability and dynamic topology. As such, we propose a sustainable and service-differentiable framework named Federated Cross-orbit Satellite Network (FCSN). Different from most existing solutions which focused on the Internet or simple cooperation among satellites, the FCSN orchestrates network resources in the dynamic topology to improve sustainability, through service-differentiable offloading in the resource-limited scenario. We formulate the sustainability-oriented federated offloading problem based on the utility and cost models tailored for the FCSN and propose an efficient hardware-budget constrained auction algorithm with a bounded approximation ratio. Finally, we design a truthful and rational payment scheme to motivate the construction of the FCSN. Extensive simulation results based on real-world deployments show that our solution significantly improves sustainability and delay, making it one step further toward the vision of the federated network of satellite networks.

For the recent two years, companies such as Starlink, Kuiper, and Telesat are launching low earth orbit (LEO) satellites to form LEO satellite mega-constellations. Unfortunately, the LEO satellite mega-constellations are not sustainable in the long term since their large size makes LEO congested, causing issues such as satellite brightness, satellite conjunction, and space debris. The issues become worse as LEO satellites have shorter battery lifespans and experience drag force, which shortens the satellite life and produces more space debris objects when LEO satellites reach the end of life. To address the issues, we propose deploying higher-orbit satellites to form a satellite-based sustainable multi-tier space network (SMTSN) instead of launching a massive number of LEO satellites. In this paper, we model the costs and gains for routing traffic with our SMTSN framework. We propose a solution to find the optimal routing paths and an efficient distributed coverage-aware (EDCA) algorithm to predict the number of skipped LEO satellites when the traffic is routed through a higher-orbit satellite. We run extensive simulations to compare the LEO satellite constellations with and without our SMTSN framework, and the results show a significant improvement in the battery cell cycle life consumption with the SMTSN framework.