Next generation cloud and edge computing architectures for Real-Time Space Data Processing and Analytics

Aderinto, Abdulquadir Babawale (2025) Next generation cloud and edge computing architectures for Real-Time Space Data Processing and Analytics. World Journal of Advanced Research and Reviews, 25 (3). pp. 152-170. ISSN 2581-9615

The rapid expansion of space exploration, satellite-based Earth observation, and interplanetary missions necessitates advanced computing architectures capable of handling massive, real-time data streams. Traditional centralized cloud computing models face significant challenges in terms of latency, bandwidth constraints, and reliability, especially for deep-space missions and large-scale satellite constellations. This study explores next-generation cloud and edge computing architectures designed to optimize real-time space data processing and analytics. By leveraging edge computing at satellite nodes and ground stations, data preprocessing, anomaly detection, and decision-making can occur closer to the source, reducing transmission delays and minimizing dependency on Earth-based infrastructure. Emerging technologies such as AI-driven edge inference, federated learning, and containerized microservices enhance computational efficiency and security in distributed space systems. Hybrid cloud-edge frameworks, integrating spaceborne data centers with terrestrial high-performance computing (HPC) facilities, offer scalability and adaptability for mission-critical applications. The implementation of 5G and future 6G-enabled space communication networks further accelerates real-time data exchange and collaborative processing between satellites and ground stations. Additionally, decentralized architectures using blockchain technology ensure data integrity and security, particularly for multi-tenant satellite networks and space commerce operations. Quantum computing advancements hold promise for accelerating complex data analytics tasks such as gravitational modeling and deep-space signal processing. This paper presents a comprehensive framework combining cloud and edge computing paradigms to enable autonomous decision-making, rapid situational awareness, and enhanced mission resilience. As space activities become increasingly data-intensive, deploying intelligent, adaptive computing infrastructures is crucial for ensuring the success of future space exploration and satellite applications.