Computation Offloading Strategies in Integrated Terrestrial and Non-Terrestrial Networks

TL;DR

IT-NTNs address rising demands for low-latency computation by integrating terrestrial networks with UAVs, HAPs, and LEO satellites to enable distributed offloading and edge processing. The chapter surveys MEC and IT-NTN architectures, compares edge, cloud, and hybrid offloading, and highlights enabling technologies such as NOMA, RSMA, mmWave/THz, and RIS, along with resource allocation, offloading decisions, and mobility management algorithms. It demonstrates applications across autonomous driving, remote healthcare, disaster response, smart agriculture, and IIoT, and discusses challenges in resource management, mobility, security/privacy, and standardization while outlining future directions like predictive mobility, blockchain, and AI at the edge. Collectively, IT-NTNs offer the potential to redefine 6G by providing ubiquitous, low-latency computation and enabling new capabilities across industries.

Abstract

The rapid growth of computation-intensive applications like augmented reality, autonomous driving, remote healthcare, and smart cities has exposed the limitations of traditional terrestrial networks, particularly in terms of inadequate coverage, limited capacity, and high latency in remote areas. This chapter explores how integrated terrestrial and non-terrestrial networks (IT-NTNs) can address these challenges and enable efficient computation offloading. We examine mobile edge computing (MEC) and its evolution toward multiple-access edge computing, highlighting the critical role computation offloading plays for resource-constrained devices. We then discuss the architecture of IT-NTNs, focusing on how terrestrial base stations, unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and LEO satellites work together to deliver ubiquitous connectivity. Furthermore, we analyze various computation offloading strategies, including edge, cloud, and hybrid offloading, outlining their strengths and weaknesses. Key enabling technologies such as NOMA, mmWave/THz communication, and reconfigurable intelligent surfaces (RIS) are also explored as essential components of existing algorithms for resource allocation, task offloading decisions, and mobility management. Finally, we conclude by highlighting the transformative impact of computation offloading in IT-NTNs across diverse application areas and discuss key challenges and future research directions, emphasizing the potential of these networks to revolutionize communication and computation paradigms.

Figures (2)

• Figure 1: Execution delay difference without optimization in NOMA-MEC enabled aerial-terrestrial network 10622807.
• Figure 2: Execution delay difference with power and cores optimization in NOMA-MEC enabled aerial-terrestrial network 10622807.