Open Access

ARTICLE

Optimizing Routing Algorithms for Next-Generation Networks: A Resilience-Driven Framework for Space-Air-Ground Integrated Networks

Peiying Zhang^1,2, Yihong Yu^1,2, Jia Luo^3,4,*, Nguyen Gia Ba⁵, Lizhuang Tan^6,7, Lei Shi⁸

1 Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao, 266580, China
2 Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software, Qingdao, 266580, China
3 College of Economics and Management, Beijing University of Technology, Beijing, 100124, China
4 Chongqing Research Institute, Beijing University of Technology, Chongqing, 401121, China
5 Faculty of Information Technology, Hung Yen University of Technology and Education, Hung Yen, 17000, Vietnam
6 Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
7 Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science, Jinan, 250014, China
8 State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China

* Corresponding Author: Jia Luo. Email:

(This article belongs to the Special Issue: AI-Driven Next-Generation Networks: Innovations, Challenges, and Applications)

Computers, Materials & Continua 2026, 87(2), 50 https://doi.org/10.32604/cmc.2026.076690

Received 25 November 2025; Accepted 04 January 2026; Issue published 12 March 2026

Abstract

Next-Generation Networks (NGNs) demand high resilience, dynamic adaptability, and efficient resource utilization to enable ubiquitous connectivity. In this context, the Space-Air-Ground Integrated Network (SAGIN) architecture is uniquely positioned to meet these requirements. However, conventional NGN routing algorithms often fail to account for SAGIN’s intrinsic characteristics, such as its heterogeneous structure, dynamic topology, and constrained resources, leading to suboptimal performance under disruptions such as node failures or cyberattacks. To meet these demands for SAGIN, this study proposes a resilience-oriented routing optimization framework featuring dynamic weighting and multi-objective evaluation. Methodologically, we define three core routing performance metrics, quantified through a four-dimensional model, encompassing robustness Rd, resilience Rr, adaptability Ra, and resource utilization efficiency Ru, and integrate them into a comprehensive evaluation metric. In simulated SAGIN environments, the proposed Multi-Indicator Weighted Resilience Evaluation Algorithm (MIW-REA) demonstrates significant improvements in resilience enhancement, recovery acceleration, and resource optimization. It maintains 82.3% service availability even with a 30% node failure rate, reduces Distributed Denial of Service (DDoS) attack recovery time by 43%, decreases bandwidth waste by 23.4%, and lowers energy consumption by 18.9%. By addressing challenges unique to the SAGIN network, this research provides a flexible real-time solution for NGN routing optimization that balances resilience, efficiency, and adaptability, advancing the field.

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Keywords

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