A Survey on Resource Management in Joint Communication and Computing-Embedded SAGIN

TL;DR

The paper surveys resource management in Joint Communication and Computing-Embedded SAGIN (JCC-SAGIN), detailing how onboard SAP computing and three-dimensional SAGIN integration reshape latency, energy, and task offloading tradeoffs. It covers architecture, hardware evolution (including HPSC and AI accelerators), enabling technologies (network slicing, EH/WPT, RIS, and DT), and a broad set of applications spanning water monitoring to disaster response. Resource modeling is formalized through metrics (e.g., task completion time and energy), offloading strategies (binary vs partial), and multi-layer network/service analysis, followed by traditional optimization methods and learning-based decision-making (MDP, DL, RL, FL, TL). The paper concludes with future directions such as coding-enhanced distributed JCC-SAGIN, hybrid multiple access, security (blockchain/quantum), and maritime integration, aiming to guide both theory and practical system design for 6G-era SAGIN. The work highlights the significance of onboard processing, RIS-enabled offloading, and DT-enabled control to achieve low-latency, energy-efficient SAGIN operations across space-air-ground strata.

Abstract

The advent of the 6G era aims for ubiquitous connectivity, with the integration of non-terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As manufacturing advances and user demands evolve, space-air-ground integrated networks (SAGIN) with computational capabilities emerge as a viable solution for services requiring low latency and high computational power. Resource management within joint communication and computing-embedded SAGIN (JCC-SAGIN) presents greater complexity than traditional terrestrial networks. This complexity arises from the spatiotemporal dynamics of network topology and service demand, the interdependency of large-scale resource variables, and intricate tradeoffs among various performance metrics. Thus, a thorough examination of resource management strategies in JCC-SAGIN is crucial, emphasizing the role of non-terrestrial platforms with processing capabilities in 6G. This paper begins by reviewing the architecture, enabling technologies, and applications in JCC-SAGIN. Then, we offer a detailed overview of resource management modeling and optimization methods, encompassing both traditional optimization approaches and learning-based intelligent decision-making frameworks. Finally, we outline the prospective research directions in JCC-SAGIN.

Figures (17)

• Figure 1: Two types of frameworks of NTN: Transparent forwarding and onboard processing.
• Figure 2: The architecture of JCC-SAGIN.
• Figure 3: How computing impacts SAGIN, and how SAGIN influences computing.
• Figure 4: Organization of this survey and the logical relationship between different sections.
• Figure 5: The performance of various aerospace-grade CPU chips is compared, highlighting chips like the TSC695F, GR712RC, and DAHLIA from Europe, RAD750 and HPSC from the USA, and BM3883 from China.